[NO.]

Year / Authors / Paper-Title / Journal / [Month]Year / [Volume-Issue-Pages] / DOI / Citation-numbers (SCI/WOS/Google-Scholar)

[311]

(2024) Doudou Guo, Weihua Xu, Weiping Ding, Yiyu Yao, Xizhao Wang, Witold Pedrycze and Yuhua Qian; Concept-Cognitive Learning Survey: Mining andFusing Knowledge fromData; Information Fusion, Accepted in April 2024 (0/0/0)

[310]

(2024) Meng Hu, Yanting Guo, Ran Wang, Xizhao Wang; Attribute reduction with fuzzy kernel-induced relations; Information Sciences; Accepted in March 2024 (0/0/0)

[309]

(2024) Chong Liu, Yi Wang, Dong Li, Xizhao Wang; Domain-incremental learning without forgetting based on random vector functional link networks; Pattern Recognition; Accepted in March 2024 (0/0/0)

[308]

(2024) Tianlun Zhang, Xinlei Zhou, Debby D. Wang, Xizhao Wang; Feature Similarity Learning Based on Fuzziness Minimization for Semi-supervised Medical Image Segmentation; Information Fusion; Accepted in January 2024 (0/0/0)

[307]

(2023) Yichao He, Jinghong Wang, Xuejing Liu, Xizhao Wang, Haibin Ouyang; Modelling and solving of knapsack problem with setup based on evolutionary algorithm; Mathematics and Computers in Simulation; December 2023; Volume: 219, Pages: 378-403; DOI: 10.1016/j.matcom.2023.12.033 (0/0/0)

[306]

(2023) Hongjie Xing, Weitao Liu, Xizhao Wang; Bounded exponential loss function based AdaBoost ensemble of OCSVMs; Pattern Recognition; Accepted in December 2023; DOI: https://doi.org/10.1016/j.patcog.2023.110191 (0/0/0)

[305]

(2023) Shuyue Chen, Jiaolv Wu, Jian Lu, Xizhao Wang; A mathematical model for efficient extraction of key locations from point-cloud data in track area; Industrial Artificial Intelligence; Accepted in July 2023; DOI: https://doi.org/10.1007/s44244-023-00011-5 (0/0/0)

[304]

(2023) Zhiming Liu, Jinhai Li, Xiao Zhang, Xizhao Wang; Incremental Incomplete Concept-Cognitive Learning Model: A Stochastic Strategy; IEEE Transactions on Neural Networks and Learning Systems; Accepted in November 2023; DOI: 10.1109/TNNLS.2023.3333537 (0/0/0)

[303]

(2023) Yan Li, Xiaoxue Wu, Xizhao Wang; Incremental reduction methods based on granular ball neighborhood rough sets and attribute grouping; International Journal of Approximate Reasoning, Accepted in July 2023; DOI: https://doi.org/10.1016/j.ijar.2023.108974 (0/0/0)

[302]

(2023) Si Cen, Xizhao Wang, Xiaoying, Chao Liu, Guoquan Dai; New Attention Strategy for Negative Sampling in Knowledge Graph Embedding; Applied Intelligence, Accepted in July 2023; DOI: 10.1007/s10489-023-04901-0 (0/0/0)

[301]

(2023) Tianlun Zhang and Xizhao Wang; Anchor-Wise Fuzziness Modeling in Convolution-Transformer Neural Networks for Left Atrium Image Segmentation; IEEE Transactions on Fuzzy Systems; Accepted in July 2023; Volume: 32, Issue: 2; Page(s): 398-408; DOI:10.1109/TFUZZ.2023.3298904 (0/0/0)

[300]

(2023) Qin Wang, Jingna Liu, Wenwu Guo and Xizhao Wang; Evolving stochastic configure network: A more compact model with interpretability; Information Sciences; Accepted in April 2023

[299]

(2023) Kaijian Chen，Jingna Liu，Wenwu Guo, Xizhao Wang; A two-stage approach based on Bayesian deep learning for predicting remaining useful life of rolling element bearings; Computers and Electrical Engineering; Accepted in April 2023

[298]

(2023) Jie Zhou, Can Gao, Xizhao Wang, Zhihui Lai, Jun Wan, Xiaodong Yue, Typicality-Aware Adaptive Similarity Matrix for Unsupervised Learning; IEEE Transactions on Neural Networks and Learning Systems; Accepted in February 2023 (0/0/0)

[297]

(2023) Arun Kumar, Xizhao Wang, et al; Guest Editorial Cognitive Cyber-Physical Systems with AI Based Solutions in Medical Informatics IEEE Journal of Biomedical and Health Informatics, FEBRUARY 2023, Volume: 27, Issue: 2, Pages: 586-587, DOI: 10.1109/JBHI.2023.3234603 (0/0/0)

[296]

(2023) Hufsa Khan, Han Liu, Xizhao Wang; A Study on relationship between prediction uncertainty and robustness to noisy data; International Journal of Systems Science (TSYS), Accepted in January 2023 (0/0/0)

[295]

(2023) Min Wang; Peng Zhao; Xin Lu; Fan Min; Xizhao Wang; Fine-Grained Visual Categorization: A Spatial–Frequency Feature Fusion Perspective; IEEE Transactions on Circuits and Systems for Video Technology; JUNE 2023; Volume: 33, Issue: 6; Page(s): 2798-2812; Digital Object Identifier: 10.1109/TCSVT.2022.3227737 (0/0/0)

[294]

(2023) Jianhua Dai, Xiongtao Zou, Yuhua Qian, Xizhao Wang; Multi-Fuzzy Beta-Covering Approximation Spaces and Their Information Measures; IEEE Transactions on Fuzzy Systems, March 2023, 31(3): 955-969; DOI: 10.1109/TFUZZ.2022.3193448 (0/0/0)

[293]

(2023) Wentao Li, Haoxiang Zhou, Weihua Xu, Xizhao Wang, Witold Pedrycz; Interval Dominance-Based Feature Selection for Interval-Valued Ordered Data; IEEE Transactions on Neural Networks and Learning Systems; October 2023; Volume: 34, Number: 10, Page(s):6898-6912, DOI: 10.1109/TNNLS.2022.3184120.

[292]

(2023) Min Wang, Chunyu Yang, Fei Zhao, Fan Min, Xizhao Wang; Cost-Sensitive Active Learning for Incomplete Data: IEEE Transactions on Systems, Man, and Cybernetics: Systems; January 2023; Volume: 53, Issue: 1; Pages 405-416; DOI: 10.1109/TSMC.2022.3182122

[291]

(2023) Haojing Shen, Sihong Chen, Ran Wang, Xizhao Wang(*). Adversarial Learning with Cost-Sensitive Classes. IEEE Transactions on Cybernetics. AUGUST 2023, Volume: 53, Issue: 8, Page(s): 4855-4866 ; DOI: https://doi.org/10.1109/TCYB.2022.3146388 (0/0/0)

[290]

(2022) Shiping Wang, Xincan Lin, Yiqing Shi, Xizhao Wang; Algorithm for orthogonal matrix nearness and its application to feature representation; Information Sciences; Accepted in December 2022 (0/0/0)

[289]

(2022) Xinlei Zhou, Sudong Chen, Nianjiao Peng, Xinpeng Zhou and Xizhao Wang; Uncertainty Guided Pruning of Classification Model Tree; Knowledge-Based Systems; Accepted in October 2022 (0/0/0)

[288]

(2022) Weipeng Cao, Yuhao Wu, Chengchao Huang, Muhammed J. A. Patwary and Xizhao Wang; MFF: Multi-Modal Feature Fusion for Zero-Shot Learning; Neurocomputing; Accepted in September 2022 (0/0/0)

[287]

(2022) Chao Liu, Xizhao Wang, Han Liu, Xiaoying Zou, Si Cen, and Guoquan Dai; Learning to Recommend Journals for Submission Based on Embedding Models; Neurocomputing; Accepted in August 2022

[286]

(2022) Shuyue Chen, Ran Wang, Jian Lu, and Xizhao Wang; Stable Matching-Based Two-Way Selection in Multi-Label Active Learning with Imbalanced Data; Information Sciences; Accepted in July 2022 (0/0/0)

[285]

(2022) Yanting Guo, Meng Hu, Xizhao Wang, Eric C.C. Tsang, Degang Chen, and Weihua Xu; A robust approach to attribute reduction based on double fuzzy consistency measure; Knowledge-Based Systems; Accepted in July 2022 (0/0/0)

[284]

(2022) Ying Zhao, Shuang Li, Rui Zhang, Chi Harold Liu, Weipeng Cao, Xizhao Wang and Song Tian; Semantic Correlation Transfer for Heterogeneous Domain Adaptation; IEEE Transactions on Neural Networks and Learning Systems, Accepted in August 2022; DOI: 10.1109/TNNLS.2022.3199619 (0/0/0)

[283]

(2022) Farhad Pourpanah, Moloud Abdar, Yuxuan Luo, Xinlei Zhou, Ran Wang, Chee Peng Lim, Xizhao Wang; A Review of Generalized Zero-Shot Learning Methods; IEEE Transactions on Pattern Analysis and Machine Intelligence; Accepted in July 2022 (0/0/36)

[282]

(2022) Guoquan Dai, Xizhao Wang, Xiaoying Zou, Chao Liu, Si Cen; MRGAT: Multi-Relational Graph Attention Network for Knowledge Graph Completion; Neural Networks; Accepted in July 2022 (0/0/0)

[281]

(2022) Xiaoying Zou, Xizhao Wang, Si Cen, Guoquan Dai, Chao Liu; Knowledge graph embedding with self-adaptive double-limited loss; Knowledge-Based Systems; Accepted in June 2022. DOI: https://doi.org/10.1016/j.knosys.2022.109310 (0/0/0)

[280]

(2022) Juncheng Li, Faming Fang, Tieyong Zeng, Guixu Zhang, Xizhao Wang; Adjustable Super-Resolution Network via Deep Supervised Learning and Progressive Self-Distillation; Neurocomputing; Accepted in May 2022. (0/0/0)

[279]

(2022) Farhad Pourpanah, Ran Wang, Chee Peng Lim, Xi-Zhao Wang, Danial Yazdani, A Review of Artificial Fish Swarm Algorithms: Recent Advances and Applications, Artificial Intelligence Review. Accepted in May 2022.

[278]

(2022) Muhammed J. A. Patwary, Weipeng Cao, Xizhao Wang(*), Mohammad Ahsanul Haque. Fuzziness based semi-supervised multimodal learning for patient’s activity recognition using RGBDT videos. Applied Soft Computing. Accepted (available online) 25 February 2022. (0/0/0)

[277]

(2022) Hufsa Khan, Xizhao Wang, Han Liu(*). Handling missing data through deep convolutional neural network. Information Sciences. Accepted in February 2022. Available online 1 March 2022. https://doi.org/10.1016/j.ins.2022.02.051. (0/0/0)

[276]

(2022) Sihong Chen, Haojing Shen, Ran Wang, Xizhao Wang(*). Towards improving fast adversarial training in multi-exit network. Neural Networks. Accepted in February 2022. https://doi.org/10.1016/j.neunet.2022.02.015 (0/0/0)

[275]

(2021)Mei Yang, Yu-Xuan Zhang, Xizhao Wang and Fan Min(*). Multi-Instance Ensemble Learning with Discriminative Bags. IEEE Transactions on Systems Man & Cybernetics: Systems. Accepted in November 2021, doi: https://doi.org/10.1109/TSMC.2021.3125040 (0/0/0)

[274]

(2022) Hong Zhu, Xizhao Wang(*) and Ran Wang(*). Fuzzy Monotonic K-Nearest Neighbor versus Monotonic Fuzzy K-Nearest Neighbor. IEEE Transactions on Fuzzy Systems, September 2022, Volume 30, Issue 9, Pages 3501-3513. DOI: https://doi.org/10.1109/TFUZZ.2021.3117450 (0/0/0)

[273]

(2021) Suyun Zhao(*), Zhigang Dai, Xizhao Wang, Peng Ni, Hengheng Luo, Hong Chen, Cuiping Li, An Accelerator for Rule Induction in Fuzzy Rough Theory, IEEE Transactions on Fuzzy Systems, Vol.29 (12), 3635-3649, December 2021, DOI: https://doi.org/10.1109/TFUZZ.2021.3101935

[272]

(2021) Jianhui Pang, Yanghui Rao(*), Haoran Xie, Xizhao Wang, Fu Lee Wang, Tak-Lam Wong, Qing Li, Fast Supervised Topic Models for Short Text Emotion Detection. IEEE Transactions on Cybernetics, February 2021, 51(2): 815-828, doi: https://doi.org/10.1109/TCYB.2019.2940520 (4/4/13)

[271]

(2020) Dongmei Mo, Zhihui Lai, Waikeung Wong(*), Xizhao Wang. Jointly Sparse Locality Regression for Image Feature Extraction. IEEE Transactions on Multimedia, November 2020, 22(11): 2873-2888, doi: https:// doi.org/10.1109/TMM.2019.2961508 (0/0/1)

[270]

(2020) Lei Zhang(*), Qingyan Duan, David Zhang, Wei Jia, Xizhao Wang. AdvKin: Adversarial Convolutional Network for Kinship Verification. IEEE Transactions on Cybernetics, December 2021, 51(12):5883-5896, 1-14 doi: https:// doi.org/10.1109/TCYB.2019.2959403 (7/7/16)

[269]

(2019) Qin Lin, Huailing Zhang, Xizhao Wang(*), Yun Xue, Hongxin Liu, Changwei Gong. A Novel Parallel Biclustering Approach and Its Application to Identify and Segment Highly Profitable Telecom Customers. IEEE Access, December 2019, 7(1): 28696-28711, doi: https://doi.org/10.1109/ACCESS.2019.2898644 (2/2/7)

[268]

(2019) Rong Chen, Shikai Guo, Xizhao Wang(*), Tianlun Zhang. Fusion of Multi-RSMOTE with Fuzzy Integral to Classify Bug Reports with an Imbalanced Distribution. IEEE Transactions on Fuzzy Systems, December 2019, 27(12):2406-2420, doi: https://doi.org/10.1109/TFUZZ.2019.2899809 (49/49/55)

[267]

(2019) Salim Rezvani, Xizhao Wang(*), Farhad Pourpanah. Intuitionistic Fuzzy Twin Support Vector Machines. IEEE Transactions on Fuzzy Systems, November 2019, 27(11):2140-2151, doi: https://doi.org/10.1109/TFUZZ.2019.2893863 (26/28/41)

[266]

(2019)Laizhong Cui, Chong Xu, Shu Yang(*), Joshua Zhexue Huang, Jianqiang Li, Xizhao Wang, Zhong Ming, Nan Lu. Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things. IEEE Internet of Things Journal, June 2019, 6(3): 4791-4803, doi: https://doi.org/10.1109/JIOT.2018.2869226 (40/42/59)

[265]

(2019) Wing W.Y. Ng, Xing Tian(*), Witold Pedrycz, Xizhao Wang, Daniel S. Yeung. Incremental Hash-bit Learning for Semantic Image Retrieval in Non-stationary Environments. IEEE Transactions on Cybernetics, November 2019, 49: 3844-3858, doi: https://doi.org/10.1109/TCYB.2018.2846760 (0/0/10)

[264]

(2019) Xiaojun Chen(*), Wenya Sun, Bo Wang, Zhihui Li, Xizhao Wang, Yunming Ye. Spectral Clustering of Customer Transaction Data With a Two-Level Subspace Weighting Method. IEEE Transactions on Cybernetics, September 2019, 49(9):3230-3241, doi: https://doi.org/10.1109/TCYB.2018.2836804 (9/9/19)

[263]

(2019) Wing W. Y. Ng, Jianjun Zhang, Chun Sing Lai(*), Witold Pedrycz, Loi Lei Lai(*), and Xizhao Wang. Cost-Sensitive Weighting and Imbalance-Reversed Bagging for Streaming Imbalanced and Concept Drifting in Electricity Pricing Classification. IEEE Transactions on Industrial Informatics, March 2019, 15(3):1588-1597, doi: https://doi.org/10.1109/TII.2018.2850930 (15/15/21)

[262]

(2019) Xizhao Wang, Tianlun Zhang, Ran Wang(*). Noniterative Deep Learning: Incorporating Restricted Boltzmann Machine into Multilayer Random Weight Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, July 2019, 49(7):1299-1380, doi: https://doi.org/10.1109/TSMC.2017.2701419 (35/35/68)

[261]

(2018) Yanyan Yang(*), Degang Chen, Hui Wang, Xizhao Wang. Incremental perspective for feature selection based on fuzzy rough sets. IEEE Transactions on Fuzzy Systems, June 2018, 26(3):1257-1273, doi: https://doi.org/10.1109/TFUZZ.2017.2718492 (40/42/52)

[260]

(2018) Patrick P. K. Chan, Weiwen Liu, Danni Chen, Daniel S. Yeung, Fei Zhang(*), Xizhao Wang, Chien-Chang Hsu. Face Liveness Detection Using a Flash Against 2D Spoofing Attack. IEEE Transactions on Information Forensis and Security, February 2018, 13(2):521-534, doi: https://doi.org/10.1109/TIFS.2017.2758748 (26/27/52)

[259]

(2018) Xizhao Wang, Ran Wang(*), Chen Xu. Discovering the Relationship Between Generalization and Uncertainty by Incorporating Complexity of Classification. IEEE Transactions on Cybernetics, February 2018, 48(2):703-715,doi: https://doi.org/10.1109/TCYB.2017.2653223 (71/71/85)

[258]

(2017) Changzhong Wang(*), Qinghua Hu, Xizhao Wang, Degang Chen, Yuhua Qian, Zhe Dong. Feature selection based on neighborhood discrimination index. IEEE Transactions on Neural Networks and Learning Systems, July 2017, 29(7):2986-2999, doi: https://doi.org/10.1109/TNNLS.2017.2710422 (112/124/129)

[257]

(2017) Ran Wang, Xizhao Wang (*), Sam Kwong, Chen Xu. Incorporating Diversity and Informativeness in Multiple-Instance Active Learning. IEEE Transactions on Fuzzy Systems, December 2017, 25(6): 1460-1475, doi: https://doi.org/10.1109/TFUZZ.2017.2717803 (65/66/78)

[256]

(2016) Xizhao Wang(*), Yulin He. Learning from Uncertainty for Big Data (Future Analytical Challenges and Strategies). IEEE Systems, Man, and Cybernetics Magazine, April 2016, 2(2): 26-31, doi: https://doi.org/10.1109/MSMC.2016.2557479 (2/2/39)WOS NO FOUND

[255]

(2015) Xi-zhao Wang(*), Hong-Jie Xing, Yan Li, Qiang Hua, Chun-Ru Dong, Witold Pedrycz. A Study on Relationship between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning, IEEE Transactions on Fuzzy Systems, October 2015, 23(5): 1638-1654, doi: https://doi.org/10.1109/TFUZZ.2014.2371479 (181/188/213)

[254]

(2015) Ran Wang(*), Sam Kwon, Xi-zhao Wang, Qing-Shan Jiang. Segment Based Decision Tree Induction with Continuous Valued Attributes. IEEE Transactions on Cybernetics, July 2015, 45(7): 1262-1275, doi: https://doi.org/10.1109/TCYB.2014.2348012 (53/55/57)

[253]

(2014) Xi-zhao Wang(*), Ran Wang, Hui-Min Feng, Huachao Wang. A new approach to classifier fusion based on upper integral. IEEE Transactions on Cybernetics, March 2014, 44(5): 620-635, doi: https://doi.org/10.1109/TCYB.2013.2263382 (36/36/42)

[252]

(2014) Xi-zhao Wang(*), Yu-Lin He, Dabby D. Wang. Non-Naive Bayesian Classifiers for Classification Problems with Continuous Attributes. IEEE Transactions on Cybernetics, January 2014, 44(1): 21-39, doi: https://doi.org/10.1109/TCYB.2013.2245891 (66/70/90)

[251]

(2014) Huimin Feng and Xizhao Wang(*). Performance Improvement of Classifier Fusion for Batch Samples Based on Upper Integral. Neural Networks, March 2015, 63: 87-93, doi: https://doi.org/10.1016/j.neunet.2014.11.004 (6/6/7)

[250]

(2012) Xizhao Wang(*), Lingcai Dong, Jianhui Yan. Maximum ambiguity based sample selection in fuzzy decision tree induction. IEEE Transactions on Knowledge and Data Engineering, August 2012, 24(8): 1491-1505, doi: https://doi.org/10.1109/TKDE.2011.67 (127/133/168)

[249]

(2010) Suyun Zhao(*), Eric C. C. Tsang, Degang Chen, Xizhao Wang. Building a rule-based classifier-a fuzzy-rough set approach, IEEE Transactions on Knowledge and Data Engineering, May 2010, 22(5): 624-638, doi: https://doi.org/10.1109/TKDE.2009.118 (87/93/115)

[248]

(2009) Xizhao Wang(*), Chunru Dong. Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy. IEEE Transactions on Fuzzy Systems, June2009, 17(3): 556-567, doi: https://doi.org/10.1109/TFUZZ.2008.924342 (160/161/207)

[247]

(2008) Xizhao Wang(*), Feng Guo, Xianghui Gao. Task 2 winner's solution: A Minkowski distance and nearest-unlike-neighbor distance method, within the paper “ Qiang Yang, et al, Estimating location using Wi-Fi”. IEEE Intelligent Systems, 2008, 23(1): 8-13

[246]

(2007) Daniel Yeung(*), Shuyuan Jin, Xizhao Wang. Covariance-matrix modeling and detecting various flooding attacks. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, March 2007, 37(2): 157-169, doi: https://doi.org/10.1109/TSMCA.2006.889480 (43/44/83)

[245]

(2007) DS Yeung(*), Ng Wing, Defeng Wang, Eric Tsang, Xizhao Wang. Localized generalization error model and its application to architecture selection for radial basis function neural network. IEEE Transactions on Neural Networks, September 2007, 18(5): 1294-1305, doi: https://doi.org/10.1109/TNN.2007.894058 (106/110/191)

[244]

(2005) DS Yeung(*), Degang Chen, ECC Tsang, JWT Lee, Xizhao Wang. On the generalization of fuzzy rough sets. IEEE Transactions on Fuzzy Systems, June 2005, 13(3): 343-361, doi: https://doi.org/10.1109/TFUZZ.2004.841734 (312/330/449)

[243]

(2004) ECC Tsang(*), DS Yeung, JWT Lee, DM Huang, Xizhao Wang. Refinement of generated fuzzy production rules by using a fuzzy neural network. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, February 2004, 34(1): 409-418, doi: https://doi.org/10.1109/TSMCB.2003.817033 (18/19/34)

[242]

(2004) DS Yeung(*), Xizhao Wang, ECC Tsang. Handling interaction in fuzzy production rule reasoning. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, October 2004, 34(5): 1979-1987, doi: https://doi.org/10.1109/TSMCB.2004.831460 (15/16/44)

[241]

(2003) ECC Tsang(*), DS Yeung, Xizhao Wang. OFFSS: Optimal fuzzy-valued feature subset selection. IEEE Transactions on Fuzzy Systems, April 2003, 11(2): 202-213, doi: https://doi.org/10.1109/TFUZZ.2003.809895 (36/37/69)

[240]

(2002) DS Yeung(*), Xizhao Wang. Improving performance of similarity-based clustering by feature weight learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, April 2002, 24(4): 556-561, doi: https://doi.org/10.1109/34.993562 (75/88/124)

[239]

(2001) Xizhao Wang(*), DS Yeung, ECC Tsang. A comparative study on heuristic algorithms for generating fuzzy decision trees. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, April 2001, 31(2): 215-226, doi: https://doi.org/10.1109/3477.915344 (95/99/180)

[238]

(2000) ECC Tsang(*), Xizhao Wang, DS Yeung. Improving learning accuracy of fuzzy decision trees by hybrid neural networks. IEEE Transactions on Fuzzy Systems, October 2000, 8(5): 601-614, doi: https://doi.org/10.1109/91.873583 (57/59/81)

[237]

(2021) Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng and Xizhao Wang(*). A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications. Neurocomputing. Accepted in November 2021 (0/0/0)

[236]

(2021) Salim Rezvani, Xizhao Wang(*). Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines. Information Sciences. July 2021, 578:659–682, doi: https://doi.org/10.1016/j.ins.2021.07.010 (1/1/1)

[235]

(2021) Yichao He, Xizhao Wang(*). Group theory-based optimization algorithm for solving knapsack problems. Knowledge-Based Systems. August 2021, 219: 104445, doi: https://doi.org/10.1016/j.knosys.2018.07.045 (11/12/18)

[234]

(2021) Weipeng Cao,Zhongwu Xie,Jianqiang Li,Zhiwu Xu,Zhong Ming,Xizhao Wang(*). Bidirectional Stochastic Configuration Network for Regression Problems. Neural Networks. March 2021, 140：237-246 doi: https://doi.org/10.1016/j.neunet.2021.03.016 (2/2/3)

[233]

(2020) Tianlun Zhang, Xi Yang, Xizhao Wang, Ran Wang(*). Deep Joint Neural Model for Single Image Haze Removal and Color Correction. Information Sciences, December 2020, 541:16-35, doi: https://doi.org/10.1016/j.ins.2020.05.105 (0/0/2)

[232]

(2020) Kai Zhang, Jianming Zhan(*), Xizhao Wang. TOPSIS-WAA method based on a covering-based fuzzy rough set: an application to rating problem. Information Science, October 2020, 539: 397-421, doi: https://doi.org/10.1016/j.ins.2020.06.009 (25/26/30)

[231]

(2020) Jafar Gholami, Farhad Pourpanah, Xizhao Wang(*), Feature selection based on improved binary global harmony search for data classification. Applied Soft Computing, August 2020, 93: 106402, doi: https://doi.org/10.1016/j.asoc.2020.106402 (14/14/19)

[230]

(2019)Peng Ni, Suyun Zhao(*), Xizhao Wang, Hong Chen, Cuiping Li. PARA: A Positive-region based Attribute Reduction Accelerator. Information Science, November 2019, 503: 533-550, doi: https://doi.org/10.1016/j.ins.2019.07.038 (12/13/16)

[229]

(2020) Xinlei Zhou, Xizhao Wang(*), Cong Hu, Ran Wang. An analysis on the relationship between uncertainty and misclassification rate of classifiers. Information Sciences, October 2020, 535: 16-27, doi: https://doi.org/10.1016/j.ins.2020.05.059 (1/1/3)

[228]

(2020) Peng Ni, Suyun Zhao(*), Xizhao Wang, Hong Chen, Cuiping Li, Eric C.C. Tsang. Incremental Feature Selection Based on Fuzzy Rough Sets. Information Sciences, October 2020, 536: 185-204, doi: https://doi.org/10.1016/j.ins.2020.04.038 (10/10/15)

[227]

(2020) Yuxuan Luo, Xizhao Wang(*), Weipeng Cao. A Novel Dataset-Specific Feature Extractor for Zero-Shot Learning. Neurocomputing, May 2020, 391:74-82, doi: https://doi.org/10.1016/j.neucom.2020.01.069 (4/4/6)

[226]

(2020) Xingping Xian, Tao Wu(*), Shaojie Qiao(*), Xi-Zhao Wang, Wei Wang, Yanbing Liu. NetSRE: Link predictability measuring and regulating. Knowledge-Based Systems, May 2020, 196:105800, doi: https://doi.org/10.1016/j.knosys.2020.105800 (4/4/5)

[225]

(2020) MingWen Shao(*), WeiZhi Wu, XiZhao Wang, ChangZhong Wang. Knowledge reduction methods of covering approximate spaces based on concept lattice. Knowledge-Based Systems, March 2020, 191: 105269, doi: https://doi.org/10.1016/j.knosys.2019.105269 (4/4/5)

[224]

(2020) S. Rezvani and Xizhao Wang(*). Erratum to “Entropy-based fuzzy support vector machine for imbalanced datasets" [Knowl.-Based Syst. 115 (2017) 87–99]. Knowledge-Based Systems, March 2020, 192: 105287, doi: https://doi.org/10.1016/j.knosys.2016.09.032 (0/0/3)WOS NO FOUND

[223]

(2020) Tianlun Zhang, Yang Li, Xizhao Wang(*). Gaussian prior based adaptive synthetic sampling with non-linear sample space for imbalanced learning. Knowledge-Based Systems, March 2020, 191: 105231, doi: https://doi.org/10.1016/j.knosys.2019.105231 (2/2/3)

[222]

(2019) Farhad Pourpanah, Ran Wang(*), Chee Peng Lim, Xizhao Wang, Manjeevan Seera, Choo Jun Tan. An Improved Fuzzy ARTMAP and Q-Learning Agent Model for Pattern Classification. Neurocomputing, September 2019, 359: 139-152, doi: https://doi.org/10.1016/j.neucom.2019.06.002 (10/10/17)

[221]

(2019) Dasen Yan, Xinlei Zhou, Xizhao Wang, Ran Wang(*). An Off-centered Technique: Learning a Feature Transformation to Improve the Performance of Clustering and Classification. Information Science, November 2019, 503: 635-651, doi: https://doi.org/10.1016/j.ins.2019.06.068 (2/2/3)

[220]

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(2019) Farhad Pourpanah(*), Chee Peng Lim, Xizhao Wang, Choo Jun Tan, Manjeevan Seera, Yuhui Shi. A hybrid model of fuzzy min–max and brain storm optimization for feature selection and data classification. Neurocomputing, March 2019, 333: 440-45, doi: https://doi.org/10.1016/j.neucom.2019.01.011 (24/24/36)

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(2019) Yichao He, Xizhao Wang(*), Suogang Gao. Ring Theory-Based Evolutionary Algorithm and its application to D{0–1}KP. Applied Soft Computing, April 2019, 77: 714–22, doi: https://doi.org/10.1016/j.asoc.2019.01.049 (5/5/9)

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(2018) Laizhong Cui, Kai Zhang, Genghui Li(*), XiZhao Wang, Shu Yang. A smart artificial bee colony algorithm with distance-fitness-based neighbor search and its application. Future Generation Computer Systems, December 2018, 89:478-493, doi: https://doi.org/10.1016/j.future.2018.06.054 (15/15/18)

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(2018) Zhi Wang and Xizhao Wang(*). A deep stochastic weight assignment network and its application to chess playing. Journal of Parallel and Distributed Computing, July 2018, 117: 205-211, doi: https://doi.org/10.1016/j.jpdc.2017.08.013 (8/8/9)

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(2018) Wing W.Y. Ng, Xiancheng Zhou, Xing Tian(*), Xizhao Wang, Daniel S. Yeung. Bagging–boosting-based semi-supervised multi-hashing with query-adaptive re-ranking. Neurocomputing, January 2018, 275:916-923, doi: https://doi.org/10.1016/j.neucom.2017.09.042 (17/18/22)

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(2018) Yichao He, Haoran Xie, Tak-Lam Wong, Xizhao Wang(*), A novel binary artificial bee colony algorithm for the set-union knapsack problem, Future Generation Computer Systems, January 2018, 78: 77-86, doi: https://doi.org/10.1016/j.future.2017.05.044 (50/56/72)

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(2018) Weipeng Cao, Xizhao Wang(*), Zhong Ming, Jinzhu Gao. A Review on Neural Networks with Random Weights. Neurocomputing, January 2018, 275:278–287, doi: https://doi.org/10.1016/j.neucom.2017.08.040 (180/182/272)

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(2017) Rana Aamir Raza Ashfaq, Xi-Zhao Wang(*), Joshua Zhexue Huang, Haider Abbas, Yu-Lin He. Fuzziness based semi-supervised learning approach for intrusion detection system. Information Sciences, February 2017, 378: 484–497, doi: https://doi.org/10.1016/j.ins.2016.04.019 (259/273/466)

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(2017) Hong-Jie Xing(*), Xi-Zhao Wang. Selective ensemble of SVDDs with Renyi entropy based diversity measure. Pattern Recognition, January 2017, 61: 185-196. doi: https://doi.org/10.1016/j.patcog.2016.07.038 (11/12/11)

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(2016) Junhai Zhai(*), Xizhao Wang, Xiaohe Pang. Voting-based Instance Selection from Large Data Sets with MapReduce and Random Weight Networks. Information Sciences, November 2016, 367: 1066–1077, doi: https://doi.org/10.1016/j.ins.2016.07.026 (34/38/43)

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(2016) Yi-Chao He, Xi-zhao Wang(*), Yu-Lin He, Shu-Liang Zhao, Wen-Bin Li. Exact and approximate algorithms for discounted {0-1} knapsack problem. Information Sciences, November 2016, 369: 634–647, doi: https://doi.org/10.1016/j.ins.2016.07.03 (22/34/37)

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(2016) Yu-Lin He, Xi-zhao Wang(*), Joshua Zhexue Huang, Fuzzy nonlinear regression analysis using a random weight network, Information Sciences, October 2016, 364: 222-240, doi: https://doi.org/10.1016/j.ins.2016.01.037 (98/98/113)

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(2016) Huanyu Zhao, Zhaowei Dong, Tongliang Li(*), Xizhao Wang, Chaoyi Pang. Segmenting time series with connected lines under maximum error bound. Information Sciences, June 2016, 345:1-8, doi: https://doi.org/10.1016/j.ins.2015.09.017 (14/15/19)

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(2015) Xi-zhao Wang(*), Zhe-Xue Huang. Editorial: Uncertainty in learning from big data. Fuzzy Sets and Systems, January 2015, 258: 1-4, doi: https://doi.org/10.1016/j.fss.2014.10.010 (16/16/28)

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(2015) Shuxia Lu(*), Xi-zhao Wang, Guiqiang Zhanga and Xu Zhoua. Effective algorithms of the Moore-Penrose inverse matrices for extreme learning machine. Intelligent Data Analysis, Augest 2015, 19(4): 743–760, doi: https://doi.org/10.3233/IDA-150743 (67/70/77)

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(2014) Yulin He(*), Ran Wang, Sam Kwong, Xizhao Wang. Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis. Information Sciences, February 2014, 259(3):252-268, doi: https://doi.org/10.1016/j.ins.2013.09.003 (46/55/62)

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(2014) Chunru Dong, Wing W.Y. Ng(*), Xizhao Wang, Patrick P.K.Chan, Daniel S.Yeung. An improved differential evolution and its application to determining feature weights in similarity-based Clustering. Neurocomputing, December 2014, 146: 95-103, doi: https://doi.org/10.1016/j.neucom.2014.04.065 (19/19/28)

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(2014) Aimin Fu, Xizhao Wang, Yulin He(*), Laisheng Wang. A study on residence error of training an extreme learning machine and its application to evolutionary algorithms. Neurocomputing, December 2014, 146(1): 75-82, doi: https://doi.org/10.1016/j.neucom.2014.04.067 (15/16/17)

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(2014) Hongyan Ji, Xizhao Wang(*), Yulin He, Wenliang Li. A study on relationships between heuristics and optimal cuts in decision tree induction. Computers and Electrical Engineering, July 2014, 40: 1429-1438, doi: https://doi.org/10.1016/j.compeleceng.2013.11.030 (1/1/2)

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(2013) Lisha Hu(*), Shuxia Lu(*), Xizhao Wang. A New and Informative Active Learning Approach for Support Vector Machine. Information Sciences, September 2013, 244: 142-160, doi: https://doi.org/10.1016/j.ins.2013.05.010 (21/24/28)

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(2013) Suyun Zhao(*), Xizhao Wang. Degang Chen and Eric Tsang. Nested structure in parameterized rough reduction, November 2013, 248: 130-150, doi: https://doi.org/10.1016/j.ins.2013.05.039 (25/28/28)

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(2013) Xizhao Wang(*), Qingyan Shao, Miao Qing, Junhai Zhai. Architecture selection for networks trained with extreme learning machine using localized generalization error model. Neurocomputing, February 2013, 102: 3-9, doi: https://doi.org/10.1016/j.neucom.2011.11053 (74/76/102)

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(2012) Qiang Hua(*), Lijie Bai, Xizhao Wang. Local similarity and diversity preserving discriminant projection for face and handwriting digits recognition. NeuroComputing, June 2012, 86:150-157, doi: https://doi.org/10.1016/j.neucom.2012.01.031 (18/19/19)

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(2012) Yulin He(*), James N. K. Liu, Xizhao Wang, YanXing Hu. Optimal bandwidth selection for re-substitution entropy estimation. Applied Mathematics and Computation, December 2012, 219(8): 3425-3460, doi: https://doi.org/10.1016/j.amc.2012.08.056 (7/9/14)

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(2011) Xizhao Wang, Yulin He, Lingcai Dong, HuanYu Zhao(*). Particle swarm optimization for determining fuzzy measures from data. Information Sciences, October 2011, 181(19): 4230-4252, doi: https://doi.org/10.1016/j.ins.2011.06.002 (101/104/133)

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(2011) Xizhao Wang(*), Aixia Chen, Huimin Feng. Upper integral network with extreme learning mechanism. Neurocomputing, September 2011, 74(16): 2520-2525, doi: https://doi.org/10.1016/j.neucom.2010.12.034 (81/82/96)

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(2008) Xizhao Wang(*), Chunguo Li, Daniel SoYeung, ShiJiSong, HuiMinFeng. A Definition of Partial Derivative of Random Functions and Its Application to RBFNN Sensitivity Analysis. Neurocomputing, March 2008, 71(7-9): 1515-1526, doi: https://doi.org/10.1016/j.neucom.2007.05.005 (12/12/24)

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(2008) Ng Wing(*), DS. Yeung, M Firth, ECC Tsang, Xizhao Wang. Feature Selection Using Localized Generalization Error for Supervised Classification Problems Using RBFNN. Pattern Recognition, December 2008, 41(12): 3706-3719, doi: https://doi.org/10.1016/j.patcog.2008.05.004 (53/56/94)

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(2007) Xizhao Wang(*), Chunru Dong, Tiegang Fan. Training T-S norm neural networks to refine weights for fuzzy if-then rules. Neurocomputing, August 2007, 70(13-15): 2581-2587, doi: https://doi.org/10.1016/j.neucom.2007.01.005 (36/38/43)

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(2007) Degang Chen(*), Qiang He, Xizhao Wang. On Linear Separability of Data Sets in Feature Space. Neurocomputing, August 2007, 70(13): 2441-2448, doi: https://doi.org/10.1016/j.neucom.2006.12.002 (17/18/29)

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(2007) Shuyuan Jin(*), DS Yeung, Xizhao Wang. Network Intrusion Detection in Covariance Feature Space. Pattern Recognition, August 2007, 40(8): 2185-2197, doi: https://doi.org/10.1016/j.patcog.2006.12.010 (33/34/111)

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(2005) Xizhao Wang(*), Qiang He, Degang Chen, Daniel Yeung. A genetic algorithm for solving the inverse problem of support vector machines. Neurocomputing, October 2005, 68: 225-238, doi: https://doi.org/10.1016/j.neucom.2005.05.006 (64/65/75)

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(2004) Xizhao Wang(*), Yadong Wang, Lijuan Wang. Improving fuzzy c-means clustering based on feature-weight learning. Pattern Recognition Letters, July 2004, 25(10): 1123-1132, doi: https://doi.org/10.1016/j.patrec.2004.03.008 (199/240/403)

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(2003) Minghu Ha(*), Xizhao Wang, Lanzhen Yang, Yan Li. Sequences of (S) fuzzy integrable functions. Fuzzy Sets and Systems, September 2003, 138(3): 507-522, doi: https://doi.org/10.1016/S0165-0114(02)00363-9 (5/5/12)

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(2001) Xizhao Wang(*), Yadong Wang, X F Xu, W D Ling, Daniel S. Yeung. A new approach to fuzzy rule generation: fuzzy extension matrix. Fuzzy Sets and Systems, November 2001, 123(3): 291-306, doi: https://doi.org/10.1016/S0165-0114(01)00002-1 (40/41/67)

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(2001) Xizhao Wang(*), Zimian Zhong, Minghu Ha. Iteration algorithms for solving a system of fuzzy linear equations. Fuzzy Sets and Systems, April 2001, 119(1):121-128, doi: https://doi.org/10.1016/S0165-0114(98)00284-X (52/57/96)

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(2000) Xizhao Wang(*), Bin Chen, Guoliang Qian, Feng Ye. On the optimization of fuzzy decision trees. Fuzzy Sets and Systems, May 2000, 112(1): 117-125, doi: https://doi.org/10.1016/S0165-0114(97)00386-2 (100/111/200)

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(1998) Minghu Ha(*), Xizhao Wang, Congxin Wu. Fundamental convergence of sequences of measurable functions on fuzzy measure space. Fuzzy Sets and Systems, April 1998, 95(1): 77-81, doi: https://doi.org/10.1016/S0165-0114(96)00314-4 (10/13/18)

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(1998) Xizhao Wang(*), Jiarong Hong. On the handling of fuzziness for continuous-valued attributes in decision tree generation. Fuzzy Sets and Systems, November 1998, 99(3): 283-290, doi: https://doi.org/10.1016/S0165-0114(97)00030-4 (44/46/77)

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(1997) Minghu Ha(*), Xizhao Wang. Some notes on the regularity of fuzzy measures on metric spaces. Fuzzy Sets and Systems, May 1997, 87(3): 385-387, doi: https://doi.org/10.1016/S0165-0114(96)00161-3 (7/7/14)

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(2020) Xizhao Wang(*), Jinhai Li. New advances in three way decision, granular computing and concept lattice. International Journal of Machine Learning and Cybernetics, May 2020, 11:945–946, doi: https://doi.org/10.1007/s13042-020-01117-3 (8/8/11)

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(2014) James N. K. Liu(*), Yulin He, Edward H. Y. Lim, Xizhao Wang. Domain ontology graph model and its application in Chinese text classification. Neural Computing and Applications, March 2014, 24(3-4): 779-798, doi: https://doi.org/10.1007/s00521-012-1272-z (8/9/24)

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(2014) Xi-zhao Wang(*), Hui Wang. Guest editorial: learning from uncertainty and its application to intelligent systems of web information. World Wide Web-internet Web Information Systems, September 2014, 17(5): 1027-1028, doi: https://doi.org/10.1007/s11280-013-0255-z (0/0/0)

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(2007) Xizhao Wang(*)，Sufang Zhang, Junhai Zhai. A nonlinear integral defined on partition and its application to decision trees. Soft Computing, February 2007, 11(4): 317-321, doi: https://doi.org/10.1007/s00500-006-0083-5 (8/8/8)

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(2007) Yan Li(*), Xizhao Wang, Minghu Ha. An on-line Multi-CBR agent dispatching algorithm.Soft Computing, June 2007,11(1): 1-5, doi: https://doi.org/10.1007/s00500-005-0032-8 (6/6/1)

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(2006) Shuyuan Jin(*), DS Yeung, Xizhao Wang, Eric C.C. Tsang. A covariance matrix based approach to Internet anomaly detection. Lecture Notes in Artificial Intelligence, 2006, 3930: 691-700, doi: https://doi.org/10.1007/11739685_72 (1/1/5)

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(2006) John W. T. Lee(*), Xizhao Wang, Jinfeng Wang. Reduction of attributes in ordinal decision systems. Lecture Notes in Artificial Intelligence, 2006, 3930: 578-587, doi: https://doi.org/10.1007/11739685_60 (0/0/1)

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(2006) Qiang He(*), Xizhao Wang, Junfen Chen, Leifan Yan. A parallel genetic algorithm for solving the inverse problem of support vector machines. Lecture Notes in Artificial Intelligence, 2006, 3930: 871-879, doi: https://doi.org/10.1007/11739685_91 (2/2/3)

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(2006) Xizhao Wang(*), Jun Shen. Using special structured fuzzy measure to represent interaction among IF-THEN rules. Lecture Notes in Artificial Intelligence, 2006, 3930: 459-466, doi: https://doi.org/10.1007/11739685_48 (1/1/4)

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(2005) Degang Chen(*), Qiang He, Xizhao Wang. The infinite polynomial kernel for support vector machine. Lecture Notes in Artificial Intelligence, 2005, 3584: 267-275, doi: https://doi.org/10.1007/11527503_32 (2/2/5)

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(2005) Xizhao Wang(*), Chunguo Li. A new definition of sensitivity for RBFNN and its applications to feature reduction. Lecture Notes in Computer Science, 2005, 3496: 81-86, doi: https://doi.org/10.1007/11427391_12 (64/64/14)

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(2004) Xizhao Wang(*), Qiang He. Enhancing generalization capability of SVM classifiers with feature weight adjustment. Lecture Notes in Computer Science, 2004, 3213: 1037-1043, doi: https://doi.org/10.1007/978-3-540-30132-5_140 (13/13/21)

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(2017) Hong Zhu, Yichao He, Xizhao Wang(*), Eric C.C. Tsang. Discrete differential evolutions for the discounted {0–1} knapsack problem. International Journal of Bio-Inspired Computation, November 2017, 10(4): 219–238, doi: https://doi.org/10.1504/IJBIC.2017.10008802 (24/30/35)

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(2008)Xizhao Wang(*), Junhai Zhai, Sufang Zhang. A model of finite-step random walk with absorbent boundaries. International Journal of Computer Mathematics, 2008, 85(11):1685-1696, doi: https://doi.org/10.1080/00207160701543400 (0/0/2)

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(2022) 王静红,梁丽娜,李昊康,王熙照; 基于标记注意力机制的社区发现算法; 山东大学学报（理学版）,2022

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(2022) 周欣蕾,王熙照;不确定性视角下的弱监督学习 西北大学学报（自然科学版）,5（52）2022,813-823

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(2022) 陈思宏,沈浩靖,王冉,王熙照.预测不确定性与对抗鲁棒性的关系研究.软件学报,2022年1月,33(2): 524-538，DOI:10.13328/j.cnki.jos.006163 (0/0/0)

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(2019) 贺毅朝, 王熙照, 张新禄, 李焕哲, 基于离散差分演化的KPC问题降维建模与求解, 计算机学报, 2019年10月, 42(10): 2249-2262 (1/1/3)

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(2018) 贺毅朝(*), 王熙照, 赵书良, 张新禄, 基于编码转换的离散演化算法设计与应用, 软件学报, 2018年9月, 29(9): 2580-2594, DOI: 10.13328/j.cnki.jos.005400 (2/7/0)

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(2017) 王熙照(*), 贺毅朝, 求解背包问题的演化算法, 软件学报, 2017年1月, 28(1): 1-16, DOI: 10.13328/j.cnki.j0s.005139 (9/23/9) [软件学报2018年高影响力论文]

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(2017) 贺毅朝(*), 王熙照, 李文斌, 赵书良，求解随机时变背包问题的精确算法与进化算法,软件学报, 2017年2月, 28(2): 185-202, DOI: 10.13328/j.cnki.jos.004937 (5/11/3)

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(2016) 王熙照，朱红，基于不确定性的大数据学习模型， 中国人工智能学会通讯，2016年11月，6(12):36-39（0/0/0）

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(2016) 王熙照(*), 邢胜, 赵士欣, 基于非平稳割点的大数据分类样例选择机制，模式识别与人工智能, 2016年9月, 29(9): 780-789, DOI: 10.16451/j.cnki.issn1003-6059.201609002 (0/0/1)

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(2016) 邢胜, 王熙照(*), 王晓兰, 基于多类重采样的非平衡数据极速学习机集成学习, 南京大学学报(自然科学), 2016年2月, 52(1): 203-211, DOI: 10.13232/j.cnki.jnju.2016.01.023 (0/1/2)

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(2016) 贺毅朝(*), 王熙照, 李文斌, 张新禄, 陈嶷瑛, 基于遗传算法求解折扣{0-1}背包问题的研究, 计算机学报, 2016年12月, 39(12):2614-2630, DOI: 10.11897/SP.J.1016.2016.02614 (18/28/13)

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(2010) 贺毅朝(*)，王熙照，刘坤起，王彦祺，差分演化的收敛性分析与算法改进, 软件学报, 2010年5月, 21(5):875-885, DOI: 10.3724/SP.J.1001.2010.03486 (49/66/65)

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(2007) 王熙照(*), 杨晨晓, 分支合并对决策树归纳学习的影响, 计算机学报, 2007年8月, 30(8): 1251-1258, DOI: 10.3321/j.issn:0254-4164.2007.08.006 (8/13/16)

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(2006) 王熙照(*), 安素芳, 基于极大模糊熵原理的模糊产生式规则权重获取研究, 计算机研究与发展, 2006年4月, 43(4): 673-678.（EI） (5/11/4)

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(2004) 王熙照(*), 赵素云, 王静红, 基于Rough集理论的模糊值属性信息表简化, 计算机研究与发展, 2004年11月, 41(11): 1974-1981.（EI） (10/15/14)

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(2004) 王熙照(*), 赵素云, 基于相似关系的模糊粗糙集模型, 计算机科学, 2004年12月, 31(z2)A: 31-35, DOI: 10.3969/j.issn.1002-137X.2004.z2.012.（EI）(0/0/0)

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(2003) 王熙照(*), 王亚东, 湛燕, 袁方, 学习特征权值对K-均值聚类算法的优化, 计算机研究与发展, 2003年6月, 40(6): 869-873.（EI）(12/18/39)

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(2000) 哈明虎(*)，王熙照，李艳，田大增，基于示例学习的模糊控制器原理，河北大学学报(自然科学版)，2000年, 20(2) :116-121, DOI: 10.7666/d.y417599 (0/0/2)

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(2000) 王熙照(*)，凌伟德，两种产生模糊决策树的启发式比较（英文），河北大学学报，2000年2月, 20 (1) :1-6 (0/0/0)

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(2000) 黄冬梅(*), 哈明虎, 王熙照, 决策树与模糊决策树的比较，河北大学学报，2000年9月，20(3): 218-221 (0/0/4)

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(1999) 叶风(*)，权光日，王熙照， 基于归结的最大一般理论特化，计算机学报，1999年12月, 22 (12) :001233-1238 (0/0/0

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(1999) 黄冬梅(*)，王熙照，一种改进的区间值属性决策树学习算法，河北大学学报（自然科学版）,1999 (4) :325-328 (0/0/1)

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(1998) 王熙照(*), 洪家荣，区间值属性决策树学习算法，软件学报, 1998年8月, 9 (8): 637-640 (6/6/10)

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(1998) 钱国良(*), 王熙照, 陈彬，手写汉字特征抽取的模糊归纳学习处理，清华大学学报（自然科学版）1998年12月，38(S2): 85-88 (0/0/0)

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(1998) 孙建平(*), 张艳娥, 王熙照，Fuzzy矩阵方程的解及性质，模糊系统与数学，1998年8月, 12(4): 72-78 (0/0/1)

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(1998) 仲自勉(*)，汪浩，王熙照，带有专家部分知识的模糊学习算法及在储层识别中的应用，河北大学学报（自然科学版）,1998年, 18(3): 215-218. (0/0/0)

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(1997) 王熙照(*), 不精确概念的表示理论(二): 抽象知识的简化与相依性, 河北大学学报, 1997，17(2): 1-5 (0/0/2)

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(1996) 王熙照(*), 不精确概念的表示理论(一): 定义与基础知识, 河北大学学报, 1996 (4): 1-6 (0/0/5)

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(1996) 王熙照(*), 哈明虎, 史本广，一类新的模糊回归模型，兰州大学学报(模糊数学与系统专辑) ,1996 (32): 472-475 (0/0/0)

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(1996) 刘会杰(*), 王熙照，模糊示例学习的一个模型及相应的决策树算法，河北大学学报(增), 1996: 1-4 (0/0/0)

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(1994) 王熙照(*), 史本广，模糊回归模型中的变量筛选，模糊系统与数学, 1994(6): 66-68 (0/0/0)

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(1994) 王熙照(*), 哈明虎，一类Fuzzy距离及在回归分析中的应用，河北大学学报, 1994(4): 8-13 (0/0/0

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(1993) 王熙照(*), 哈明虎，一类模糊线性方程组的迭代解法，模糊分析设计的理论与应用(主编：王彩华等，中国建筑工业出版社，1993) 604-605 (0/0/0)

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(1993) 王熙照(*), 哈明虎，多元Fuzzy线性回归，河北大学学报, 1993(3): 8-14 (0/0/0)

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(1992) 王熙照(*), 哈明虎，泛Fuzzy积分，河北大学学报, 1992(3): 18-24 (0/0/0)

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(1992) 王熙照(*), 哈明虎，非线性模糊模型分析及参数估计，模糊系统与数学, 1992(6): 38-41 (0/0/0)

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(1992) 王熙照(*), 哈明虎, 凌伟德，模糊数序列空间，模糊系统与数学, 1992(6): 41-43 (0/0/0)

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(1992) 哈明虎(*), 王熙照，Fuzzy测度的绝对连续性及扩张，模糊系统与数学, 1992(6): 35-37 (0/0/0)

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(1991) 王熙照(*), 哈明虎，由泛积分定义的Fuzzy测度，模糊数学与系统成果会论文集(主编：曹炳元，湖南科学技术出版社，1991) 61-63 (0/0/0)

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(1991) 哈明虎(*), 王熙照，Fuzzy线性回归分析及参数估计，模糊数学与系统成果会论文集(主编：曹炳元，湖南科学技术出版社，1991) 19-21 (0/0/0)

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(1991) 哈明虎(*), 王熙照，Fuzzy集合上Fuzzy 测度的绝对连续性及扩张，河北大学学报, 1991(4): 17-22 (0/0/0)

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(1991) 王熙照(*), 哈明虎，σ-可加模糊集上模糊测度，河北大学学报, 1991(1): 17-24 (0/0/0)

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(1990) 王熙照(*), 哈明虎，sigma-可加模糊集上的模糊测度及结构特征，中国模糊数学与模糊系统委员会第5届年会文集, (责任主编：徐扬、余孝华，西南交通大学出版社，成都，1990) 57-59 (0/0/0)

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(1989) 哈明虎(*), 王熙照, Fuzzy值变量线性回归的一种参数估计方法，河北大学学报, 1989(5): 15-19 (0/0/0)

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(1989) 哈明虎(*), 王熙照, 模糊测度与收敛, 河北大学学报, 1989(5): 79-86 (0/0/0)

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(2020) Xizhao Wang, Zhongwu Xie, Weipeng Cao(*), Zhong Ming. A Hierarchical-Tree-Based Method for Generative Zero-Shot Learning. In: Qiu M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science, vol 12453. Springer, Cham, doi: 10.1007/978-3-030-60239-0_24 (0/0/0)

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(2020) Zhongwu Xie, Weipeng Cao(*), Xizhao Wang,Zhong Ming , Jingjing Zhang(*), Jiyong Zhang. A biologically inspired feature enhancement framework for zero-shot learning;The 7th IEEE International Conference on Cyber Security and Cloud Computing (IEEE CSCloud 2020) (Accepted in May 2020) (3/1/5)

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(2019) Farhad Pourpanah, Ran Wang (*), Xizhao Wang, Yuhui Shi and Danial Yazdani, mBSO: A Multi-Population Brain Storm Optimization for Multimodal Dynamic Optimization Problems, IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China, 2019, pp. 673-679, doi: 10.1109/SSCI44817.2019.9002850 (4/2/5)

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(2019) Farhad Pourpanah, Ran Wang and Xizhao Wang(*), Feature Selection for Data Classification based on Binary Brain Storm Optimization, IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), Singapore, 2019, pp. 108-113, doi: 10.1109/CCIS48116.2019.9073751 (0/0/2)

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(2019) Weipeng Cao, Muhammed J. A. Patwary, Pengfei Yang, Xizhao Wang, Zhong Ming(*), An Initial Study on the Relationship Between Meta Features of Dataset and the Initialization of NNRW, 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 2019, pp. 1-8. DOI: 10.1109/IJCNN.2019.8852219 (9/0/13)

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(2018) S. Rezvani and Xizhao Wang(*), A New Type-2 Intuitionistic Exponential Triangular Fuzzy Number and Its Ranking Method with Centroid Concept and Euclidean Distance, 2018 IEEE Proceedings on Fuzzy Systems (FUZZ-IEEE), Rio de Janeiro, 2018, pp. 1-8. DOI: 10.1109/FUZZ-IEEE.2018.8491685 (3/1/4)

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(2016) Sheng Xing(*), Hong Zhu, Yulin He, Xizhao Wang, An Approach to Sample Selection from Big Data for Classification, IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, October 2016, Proceedings pp: 002928-002935, DOI: 10.1109/SMC.2016.7844685 (0/0/2)

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(2015) Jian Zhang(*), Junhai Zhai, Hong Zhu, Xizhao Wang, Induction of monotonic decision trees. Proceedings of 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Guangzhou, China, July 2015, Proceedings pp: 203-207, DOI: 10.1109/ICWAPR.2015.7295951 (1/1/2)

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(2015) Peizhou Zhang(*), Shixin Zhao, Xizhao Wang, The failure analysis of extreme learning machine on big data and the counter measure, Proceedings of 2015 International Conference on Machine Learning and Cybernetics (ICMLC), Guangzhou, China, July 2015, Proceedings pp: 849-853, DOI: 10.1109/ICMLC.2015.7340664 (0/0/2)

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(2015) Xin Wang(*), Junhai Zhai, Jiankai Chen, Xizhao Wang, Ordinal decision trees based on fuzzy rank entropy, Proceedings of 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), Guangzhou, China, July 2015, Proceedings pp. 208-213, DOI: 10.1109/ICWAPR.2015.7295952 (2/2/3)

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(2014) Junhai Zhai(*), Jinggeng Wang, Xizhao Wang, Ensemble online sequential extreme learning machine for large data set classification, Proceedings of 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, USA, 05-08 October 2014 , Proceedings pp. 2250-2255, DOI: 10.1109/SMC.2014.6974260 (11/8/11)

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(2014) Yan Li(*), Hongjie Xing, Qiang Hua, Xzhao Wang, Prerna Batta, Soroush Haeri, Ljiljana Trajković, Classification of BGP anomalies using decision trees and fuzzy rough sets, Proceedings of 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, USA, October 2014, Proceedings pp. 1312-1317, DOI: 10.1109/SMC.2014.6974096 (17/13/25)

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(2014) James N. K. Liu(*), Yanxing Hu, Yulin He, Xizhao Wang, Regression ensemble with PSO algorithms based fuzzy integral, Proceedings of 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, July 2014, Proceedings pp. 762-768, DOI: 10.1109/CEC.2014.6900342 (0/0/0)

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(2012) Xizhao Wang(*), Meng Zhang, Shuxia Lu, Xu Zhou, A total error rate multi-class classification, In Proceedings of 2012 International Conference on Systems, Man, and Cybernetics, Seoul, South Korea, October 2012, Proceedings pp: 964-969, doi: https://doi.org/10.1109/ICSMC.2012.6377853 (0/0/0)

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(2012) Xizhao Wang(*), Qing Miao, Mengyao Zhai, Junhai Zhai, Instance selection based on sample entropy for efficient data classification with ELM, In Proceedings of 2012 International Conference on Systems, Man, and Cybernetics, Seoul, South Korea, October 2012, Proceedings pp: 970-974, doi: https://doi.org/10.1109/ICSMC.2012.6377854 (2/2/2)

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(2011) Hongjie Xing(*), Xizhao Wang, Minghu Ha, A comparative experimental study of feature-weight learning approaches, In Proceedings of 2011 International Conference on Systems, Man, and Cybernetics, Anchorage, AK, USA, October 2011 , Proceedings pp: 3500-3505, DOI: 10.1109/ICSMC.2011.6084211 (4/3/5)

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(2011) Junhai Zhai(*), Yuanyuan Gao, Mengyao Zhai, Xizhao Wang, Rough set model and its eight extensions, In Proceedings of 2011 International Conference on Systems, Man, and Cybernetics, Anchorage, AK, USA, October 2011, Proceedings pp: 3512-3517, doi: https://doi.org/10.1109/ICSMC.2011.6084213 (0/2/3)

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(2011) James N. K. Liu(*), Yulin He, Xizhao Wang, Yanxing Hu, A comparative study among different kernel functions in flexible naïve Bayesian classification, In Proceedings of 2011 International Conference on Machine Learning and Cybernetics, Guilin, China, July 2011 Proceedings pp: 638-643, doi: https://doi.org/10.1109/ICMLC.2011.6016813 (7/0/7)

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(2010) Xizhao Wang(*), Xianghui Gao, Qiang He, Side effect of cut in decision tree generation for continuous attributes, In Proceedings of 2010 International Conference on Systems, Man, and Cybernetics, Istanbul, Turkey, October 2010, Proceedings pp: 1364-1369, doi: https://doi.org/10.1109/ICSMC.2010.5642456 (1/0/1)

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(2009) Shan Su(*), Xizhao Wang, Junhai Zhai, An Improved Cluster Oriented Fuzzy Decision Trees, In Proceedings of 2009 International Conference on Rough Sets, Fuzzy Sets , Data Mining & Granular Computing, Indian Inst Technol, Delhi, India, December 2005-2009, Proceedings pp: 447-454, doi: https://doi.org/10.1007/978-3-642-10646-0_54 (1/1/1)

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(2009) Ling-Cai Dong(*), Dan Wang, Xi-Zhao Wang, An Improved Sample Selection Algorithm in Fuzzy Decision Tree Induction, In Proceedings of 2009 International Conference on Systems, Man, and Cybernetics, San Antonio, TX, October 2009 , Proceedings pp: 629-634, doi: https://doi.org/10.1109/ICSMC.2009.5346654 (5/5/5)

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(2009) Mingzhu Lu(*), Philip Chen, Jianbing Huo, Xizhao Wang, Multi-Stage Decision Tree based on Inter-class and Inner-class Margin of SVM, In Proceedings of 2009 International Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, October 2009, Proceedings pp: 1875-1880, doi: https://doi.org/10.1109/ICSMC.2009.5346208 (12/8/18)

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(2008) Ning Zhang(*), Xizhao Wang, Tao Xiao, An Instance Selection Algorithm Based on Contribution, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, July 2008, Proceedings pp: 919-923, doi: https://doi.org/10.1109/ICMLC.2008.4620536 (1/0/3)

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(2008) Feng Guo(*), Xizhao Wang, Yan Li, A New Algorithm for Solving Convex Hull Problem and Its Application to Feature Selection, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, July 2008, Proceedings pp: 369-373, doi: https://doi.org/10.1109/ICMLC.2008.4620433 (4/3/5)

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(2008) Xizhao Wang(*), Bo Wu, Yulin He, Xianghao Pei, NRMCS: Noise Removing Based on the MCS, Proceedings of the Seventh International Conference on Machine Learning and Cyberne tics, Kunming, China, July 2008, Proceedings pp: 89-93, doi: https://doi.org/10.1109/ICMLC.2008.4620384 (10/7/12)

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(2008) Xizhao Wang(*), Junhai Zhai, Sufang Zhang, Fuzzy Decision Tree Based on the Important Degree of Fuzzy Attribute, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, China, July 2008, Proceedings pp: 511-516, doi: https://doi.org/10.1109/ICMLC.2008.4620458 (3/0/6)

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(2008) Mingzhu Lu(*), C. L. Philip Chen, Jianbing Huo, Xizhao Wang, Optimization of combined kernel function for SVM based on large margin learning theory, In Proceedings of 2008 International Conference on Systems, Man, and Cybernetics, Singapore, October 2008, Proceedings pp: 353-358, doi: https://doi.org/10.1109/ICSMC.2008.4811301 (10/5/12)

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(2008) Hongjie Xing(*), Xizhao Wang, Ruixian Zhu, Dan Wang, Application of kernel learning vector quantization to novelty detection, In Proceedings of 2008 International Conference on Systems, Man, and Cybernetics, Singapore, October 2008, Proceedings pp: 439-443, doi: https://doi.org/10.1109/ICSMC.2008.4811315 (1/0/1)

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(2007) Degang Chen(*), Xizhao Wang, Suyun Zhao, Attribute reduction based on fuzzy rough sets, Proceedings of the International Conference on Rough Sets and Intelligent Systems Paradigms, Warsaw, Poland, June 2007, Rough Sets and Intelligent Systems Paradigms, Proceedings pp: 381-390, doi: https://doi.org/10.1007/978-3-540-73451-2_40 (18/0/29)

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(2007) Weili Zhang(*), Xizhao Wang, Feature extractionand classification for human brain CT images, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, Augest 2007, Proceedings pp: 1155-1159, doi: https://doi.org/10.1109/ICMLC.2007.4370318 (0/10/39)

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(2007) Xizhao Wang(*), Weixi Lin, Application of inductive learning in human brain CT image recognition, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, Augest 2007, Proceedings pp: 1667-1671, doi: https://doi.org/10.1109/ICMLC.2007.4370415 (1/0/4)

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(2007) Xizhao Wang(*), Xiaoyan Liu, Yan Li and Chunguo Li, Norm-based localized generalization error model and its derivation for radial basis function neural networks, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, Augest 2007, Proceedings pp: 3623-3527, doi: https://doi.org/10.1109/ICMLC.2007.4370757 (0/0/1)

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(2007) Xizhao Wang(*), Bin Wu, Jie Li, An improvement for localized generalization error model, Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, China, August, 2007, Proceedings pp: 2901-2910, doi: https://doi.org/10.1109/ICMLC.2007.4370644 (1/0/1)

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(2007) Xizhao Wang(*), Jianhui Yan, Ran Wang and Chunru Dong, A sample selection algorithm in fuzzy decision tree induction and its theoretical analyses, Proceedings of 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, October 2007, Proceedings pp: 3621-3626, doi: https://doi.org/10.1109/ICSMC.2007.4413726 (10/0/14)

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(2007) Xizhao Wang(*), Shuxia Lu and Ruixian Zhu, Solving SVM inverse problems based on clustering, Proceedings of 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, October 2007, Proceedings pp: 3615-3620, doi: https://doi.org/10.1109/ICSMC.2007.4413725 (1/0/1)

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(2007) Limei Feng(*), Xizhao Wang, Improving on symbolic learning system based on genetic algorithm, Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering, Chengdu, China, October 2007, Proceedings pp: 1132-1138, doi: https://doi.org/10.2991/iske.2007.183 (0/0/0)

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(2007) Jinyan Sun(*), Xizhao Wang, A new method for constructing radial basis function neural networks, Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering, Chengdu, China, October 2007, Proceedings pp: 1240-1245, doi: https://doi.org/10.2991/iske.2007.182 (0/5/0)

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(2006) Chenxiao Yang(*), Xizhao Wang and Ruixian Zhu, A strategy of merging branches based on margin enlargement of SVM in decision tree induction, Proceedings of 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, China, October 2006, Proceedings pp: 824-828, doi: https://doi.org/10.1109/ICSMC.2006.384490 (2/0/2)

[42]

(2006) Jianbing Huo(*), Xizhao Wang, Mingzhu Lu and Junfen Chen, Induction of multi-stage decision tree, Proceedings of 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, China, October 2006, Proceedings pp: 835-839, doi: https://doi.org/10.1109/ICSMC.2006.384492 (2/1/10)

[41]

(2006) Xizhao Wang(*) ,Xianghui Gao, A research on the relation between training ambiguity and generalization capability, Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, China, August 2006, Proceedings pp:2008-2013, doi: https://doi.org/10.1109/ICMLC.2006.259133 (2/0/2)

[40]

(2006) Miao Wang(*), Xizhao Wang. A Research on Weight Acquisition of Weighted Fuzzy Production Rules Based on Genetic Algorithm. Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 2208-2211, doi: https://doi.org/10.1109/ICMLC.2006.258622 (1,0,3)

[39]

(2006) Xizhao Wang(*), Shuxia Lu. Improved fuzzy multicategory support vector machines classifier. Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 3585-3589, doi: https://doi.org/10.1109/ICMLC.2006.258575 (7,2,9)

[38]

(2006) Xizhao Wang(*), Mingzhu Lu, Jianbing Huo. Fault diagnosis of power transformer based on large margin learning classifier. Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 2886-2891, doi: https://doi.org/10.1109/ICMLC.2006.259075 (7,5,8)

[37]

(2006) Xizhao Wang(*), Feng Yang, Yan Li. A Disscussion on the Overlapping in Fuzzy Production Rule Reasoning. Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 13-16 August 2006, Proceedings pp: 4557-4562, doi: https://doi.org/10.1109/ICMLC.2006.258377 (0,0,2)

[36]

(2005) Xizhao Wang(*), Xuguang Wang, Jun Shen. The representation of interaction among fuzzy rules. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3098-3103, doi: https://doi.org/10.1109/ICMLC.2005.1527474 (0,0,0)

[35]

(2005) Xizhao Wang(*), Jun Shen, Xuguang Wang. Using 2-additive fuzzy measure to represent the interaction among if-then rules. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 2797-2801, doi: https://doi.org/10.1109/ICMLC.2005.1527418 (0,2,1)

[34]

(2005) Xizhao Wang(*), Yan Ha, Degang Chen. On the reduction of fuzzy rough sets. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3174-3178, doi: https://doi.org/10.1109/ICMLC.2005.1527489 (0,11,12)

[33]

(2005) Xizhao Wang(*), Sufang Zhang, Junhai Zhai. A nonlinear integral defined on partition of set and its fundamental properties. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3092-3097, doi: https://doi.org/10.1109/ICMLC.2005.1527473 (0,0,0)

[32]

(2005) Xizhao Wang(*),Hui Zhang. An upper bound of input perturbation for RBFNNs sensitivity analysis. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 4704-4709, doi: https://doi.org/10.1109/ICMLC.2005.1527769 (0,0,3)

[31]

(2005) Xizhao Wang(*), Ying Xu. Multilevel weighted fuzzy reasoning with interaction. Proceedings of 2005 IEEE International Conference on Systems, Man and Cybernetics, Waikoloa, HI, 10-12 October 2005, Proceedings pp: 708-715, doi: https://doi.org/10.1109/ICSMC.2005.1571230 (3,3,4)

[30]

(2005) Xizhao Wang(*), Chunguo Li. A new definition of sensitivity for RBFNN and its applications to feature reduction. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 81-86, doi: https://doi.org/10.1007/11427391_12 (12,64,14)

[29]

(2005) Juan Sun(*), Xizhao Wang. An initial comparison on noise resisting between crisp and fuzzy decision trees. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 2545-2550, doi: https://doi.org/10.1109/ICMLC.2005.1527372 (0,3,13)

[28]

(2005) John W.T. Lee(*), Xizhao Wang, Jinfeng Wang. Finding reducts for ordinal decision tables. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, Proceedings pp: 3143-3147, doi: https://doi.org/10.1109/icmlc.2005.1527483 (0,0,0)

[27]

(2004) Xizhao Wang(*), Chunru Dong, Daniel Yeung. A study on generalization capability of weighted fuzzy production rules with maximum entropy. Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics, The Hague, Netherlands, 10-13 October 2004, Proceedings pp: 3181-3186, doi: https://doi.org/10.1109/ICSMC.2004.1400829 (1,0,1)

[26]

(2004) Xizhao Wang(*), Xiaojun Wang. A new methodology for determining fuzzy densities in the fusion model based on fuzzy integral. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 2028-2031, doi: https://doi.org/10.1109/ICMLC.2004.1382128 (0,5,17)

[25]

(2004) Xizhao Wang(*), Xiaoying Lu, Feng Zhang. Feature selection based on fuzzy extension matrix for multi-class problem. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 2032-2035, doi: https://doi.org/10.1109/ICMLC.2004.1382129 (0,1,2)

[24]

(2004) Xizhao Wang(*), Junfen Chen. Multiple neural networks fusion model based on croquet fuzzy integral. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 2024-2027, doi: https://doi.org/10.1109/ICMLC.2004.1382127 (0,5,20)

[23]

(2004) Xizhao Wang(*), Huimin Feng. Nonnegative set functions in multiple classifier fusion. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 2020-2023, doi: https://doi.org/10.1109/ICMLC.2004.1382126 (0,2,6)

[22]

(2004) Wing Ng(*), Daniel Yeung, Xizhao Wang, Ian Cloete. A study of the difference between partial derivative and stochastic neural network sensitivity analysis for applications in supervised pattern classification problems. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26-29 August 2004, Proceedings pp: 4283-4288, doi: https://doi.org/10.1109/ICMLC.2004.1384590 (0,5,15)

[21]

(2003) Yong Li(*), Xizhao Wang, Qiang Hua. Using BP-network to construct fuzzy decision tree with composite attributes. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1791-1795, doi: https://doi.org/10.1109/ICMLC.2003.1259787 (0,1,6)

[20]

(2003) Yan Li(*), Xizhao Wang, Minghu Ha. On-line multi-CBR agent dispatching. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 2071-2075, doi: https://doi.org/10.1109/ICMLC.2003.1259845 (0,1,4)

[19]

(2003) Suyun Zhao(*), Xizhao Wang. A fuzzy model of rough sets. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1687-1691, doi: https://doi.org/10.1109/ICMLC.2003.1259768 (0,0,1)

[18]

(2003) Dazhong Liu(*), Xizhao Wang, J. W. T. Lee. Ordinal fuzzy sets and rough sets. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1438-1441, doi: https://doi.org/10.1109/ICMLC.2003.1259719 (0,1,1)

[17]

(2003) Qiang He(*), Xizhao Wang, Hongjie Xing. A fuzzy classification method based on support vector machine. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1237-1240, doi: https://doi.org/10.1109/ICMLC.2003.1259676 (0,0,0)

[16]

(2003) Qunfeng Zhang(*), Xizhao Wang, Jinghong Wang. A further study on simplification of decision tables. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1657-1661, doi: https://doi.org/10.1109/ICMLC.2003.1259762 (0,0,0)

[15]

(2003) Hua Li(*), Xizhao Wang, Yong Li. Using mutual information for selecting continuous-valued attribute in decision tree learning. Proceedings of 2003 International Conference on Machine Learning and Cybernetics, Xi’an, China, 2-5 November 2003, Proceedings pp: 1496-1499, doi: https://doi.org/10.1109/ICMLC.2003.1259731 (0,0,2)

[14]

(2003) Shixin Zhao(*), Xizhao Wang. Core and reduction from mutual relation view and their fuzzy generalization. Proceedings of 2003 IEEE International Conference on Systems, Man and Cybernetics, Washington, DC, USA, 6-9 October 2003, Proceedings pp: 2611-2616, doi: https://doi.org/10.1109/ICSMC.2003.1244277 (0,2,4)

[13]

(2002) Yan Li(*) , Minghu Ha, Xizhao Wang. Principle and Design of Fuzzy Controller Based on Fuzzy Learning from Examples. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1441-1446, doi: https://doi.org/10.1109/ICMLC.2002.1167445 (0,1,4)

[12]

(2002) Dongmei Huang(*), Xizhao Wang, Minghu Ha. The Optimization Problem of the Fuzzy Bi-Branches Decision Trees. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1667-1668, doi: https://doi.org/10.1109/ICMLC.2002.1167496 (0,3,3)

[11]

(2002) Dazhong Liu(*), Xizhao Wang, John W.T. Lee. Correlation Based Generating Rules for Fuzzy Classification. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1733-1736, doi: https://doi.org/10.1109/ICMLC.2002.1175333 (0,1,2)

[10]

(2002) Hongjie Xing(*), Xizhao Wang, Qiang He, Hongwei Yang. The Multistage Support Vector Machine. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1815-1818, doi: https://doi.org/10.1109/ICMLC.2002.1175353 (0,0,2)

[9]

(2002) Xizhao Wang(*), Minghua Zhao, Daniel So Yeung. Parametric Sensitivity in Building Fuzzy Decision Trees: an Experimental Analysis. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1819-1823, doi: https://doi.org/10.1109/ICMLC.2002.1175354 (0,0,1)

[8]

(2002) Xizhao Wang(*), Hongwei Yang, Minghua Zhao, Juan Sun. A Decision Tree Based on Hierarchical Decomposition. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1824-1828, doi: https://doi.org/10.1109/ICMLC.2002.1175355 (0,0,4)

[7]

(2002) Lijuan Wang(*), Xizhao Wang, Minghu Ha, Yinshan Gu. Mining the Weights of Similarity Measure Through Learning. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1837-1841, doi: https://doi.org/10.1109/ICMLC.2002.1175359 (0,0,2)

[6]

(2002) Daniel So Yeung(*), Juan Sun, Xizhao Wang. An Initial Comparison of Generalization-Capability between Crisp and Fuzzy Decision Trees. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 1846-1851, doi: https://doi.org/10.1109/ICMLC.2002.1175359 (0,2,12)

[5]

(2002) Shenshan Qiu(*), Eric C.C. Tsang, Daniel S. Yeung, Xizhao Wang. Energy Function Criterion for Discrete Hopfield-Type Neural Network with Delay. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, 4-5 November 2002, Proceedings pp: 2240-2244, doi: https://doi.org/10.1109/ICMLC.2002.1175438 (0,0,0)

[4]

(2001) Ruifeng Xu(*), D. S. Yeung, Xizhao Wang. Using neural network classifier in post-processing system for handwritten Chinese character recognition. Proceedings of 2001 IEEE International Conference on Systems, Man and Cybernetics, Tucson, AZ, USA, 07-10 October 2001, Proceedings pp: 1497-1502, doi: https://doi.org/10.1109/ICSMC.2001.973493 (0,0,7)

[3]

(2001) E. C. C. Tsang(*), D. S. Yeung, Xizhao Wang. Learning weights of fuzzy production rules by a max-min neural network. Proceedings of 2001 IEEE International Conference on Systems, Man and Cybernetics, Tucson, AZ, USA, 07-10 October 2001, Proceedings pp: 1485-1490, doi: https://doi.org/10.1109/ICSMC.2001.973493 (1,2,7)

[2]

(2000) Xizhao Wang(*), D. S. Yeung. Using fuzzy integral to modeling case based reasoning with feature interaction. Proceedings of 2000 IEEE International Conference on Systems, Man and Cybernetics, Nashville, TN, USA, 8-11 October 2000, Proceedings pp: 3660-3665, doi: https://doi.org/10.1109/ICSMC.2000.886578 (9,0,23)

[1]

(2000) D. S. Yeung(*), Xizhao Wang. Using a neuro-fuzzy technique to improve the clustering based on similarity. Proceedings of 2000 IEEE International Conference on Systems, Man and Cybernetics, Nashville, TN, USA, 8-11 October 2000, Proceedings pp: 3693-3698, doi: https://doi.org/10.1109/ICSMC.2000.886584 (1,0,9)