[NO.]

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

[90]

(2018) Huang Z, Wang X(*). Sensitivity of data matrix rank in non-iterative training. Neurocomputing, November 2018, 313(3):386–391, DOI: https://doi.org/10.1016/j.neucom.2018.06.055 (4/4/4)

[89]

(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)

[88]

(2018) Junhai Zhai(*), Xizhao Wang, Sufang Zhang, Shaoxing Houd. Tolerance rough fuzzy decision tree. Information Sciences, October 2018, 465:425-438, doi: https://doi.org/10.1016/j.ins.2018.07.006 (12/12/18)

[87]

(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)

[86]

(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)

[85]

(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)

[84]

(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)

[83]

(2017) Hongyu Zhu, Xi-Zhao Wang(*). A cost-sensitive semi-supervised learning model based on uncertainty. Neurocomputing, August 2017, 251: 106–114, doi: https://doi.org/10.1016/j.neucom.2017.04.010 (14/17/20)

[82]

(2017) Hong Zhu, Eric Tsang(*), Xizhao Wang, Rana Aamir Raza Ashfaq. Monotonic classification Extreme Learning Machine. Neurocomputing, February 2017, 225: 205–213, doi: https://doi.org/10.1016/j.neucom.2016.11.021 (26/28/35)

[81]

(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)

[80]

(2017) JinhaiLi(*), Cherukuri, Aswani Kumar, ChanglinMei, XizhaoWang. Comparison of reduction in formal decision contexts. International Journal of Approximate Reasoning, January 2017, 80: 100–122, doi: https://doi.org/10.1016/j.ijar.2016.08.007 (61/68/77)

[79]

(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)

[78]

(2016) Mingwen Shao(*), Yee Leung, Xizhao Wang, WeiZhi Wu, Granular reducts of formal fuzzy contexts, Knowledge-Based Systems, October 2016, 114:156-166, doi: https://doi.org/10.1016/j.knosys.2016.10.010 (22/30/32)

[77]

(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)

[76]

(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)

[75]

(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)

[74]

(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)

[73]

(2015) Yu-lin He(*), James N.K. Liu, Yan-xing Hu, Xi-zhao Wang. OWA operator based link prediction ensemble for social network. Expert Systems with Applications, January 2015, 42: 21-50, doi: https://doi.org/10.1016/j.eswa.2014.07.018 (92/104/113)

[72]

(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)

[71]

(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)

[70]

(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)

[69]

(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)

[68]

(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)

[67]

(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)

[66]

(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)

[65]

(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)

[64]

(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)

[63]

(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)

[62]

(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)

[61]

(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)

[60]

(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)

[59]

(2008) Xizhao Wang(*), Junhai Zhai, Shuxia Lu. Induction of multiple fuzzy decision trees based on rough set technique. Information Sciences, August 2008, 178(16): 3188-3202, doi: https://doi.org/10.1016/j.ins.2008.03.021 (132/138/174)

[58]

(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)

[57]

(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)

[56]

(2007) Xizhao Wang, Eric Tsang, Suyun Zhao(*), Degang Chen, Daniel Yeung. Learning fuzzy rules from fuzzy examples based on rough set techniques. Information Sciences, 2007, 177(20): 4493-4514, doi: https://doi.org/10.1016/j.ins.2007.04.010 (156/162/215)

[55]

(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)

[54]

(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)

[53]

(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)

[52]

(2005) Degang Chen(*), ECC Tsang, DS Yeung, Xizhao Wang. The parameterization reduction of soft sets and its applications. Computers & Mathematics with Applications, APR-MAY 2005, 49(5-6): 757-763, doi: https://doi.org/10.1016/j.camwa.2004.10.036 (417/451/919)

[51]

(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)

[50]

(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)

[49]

(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)

[48]

(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)

[47]

(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)

[46]

(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)

[45]

(1999) Xizhao Wang(*), Jiarong Hong. Learning optimization in simplifying fuzzy rules. Fuzzy Sets and Systems, September 1999, 106(3): 349-356, doi: https://doi.org/10.1016/S0165-0114(97)00300-X (46/47/66)

[44]

(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)

[43]

(1998) Xizhao Wang, Minghu Ha(*). Note on maxminmu/Eestimation. Fuzzy Sets and Systems, 1998, 94(1): 71-75, doi: https://doi.org/10.1016/S0165-0114(96)00245-X (5/7/16)

[42]

(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)

[41]

(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)

[40]

(1997) Minghu Ha(*), Lixin Cheng, Xizhao Wang. Notes on Riesz's theorem on fuzzy measure space. Fuzzy Sets and Systems, September 1997, 90(3): 361-363, doi: https://doi.org/10.1016/S0165-0114(96)00103-0 (3/5/6)

[39]

(1992) Xizhao Wang(*), Minghu Ha. Fuzzy linear regression analysis. Fuzzy Sets and Systems, October 1992, 51(2): 179-188, doi: https://doi.org/10.1016/0165-0114(92)90190-F (14/16/35)

[38]

(2020) Weipeng Cao(*), Lei Hu, Jinzhu Gao, Xizhao Wang, Zhong Ming. A study on the relationship between the rank of input data and the performance of random weight neural network. Neural Computing and Applications, January 2020, 32:12685-12696, doi: https://doi.org/10.1007/s00521-020-04719-8 (7/7/12)

[37]

(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)

[36]

(2020) Xizhao Wang(*), Yanxia Zhao, Farhad Pourpanah. Recent advances in deep learning. International Journal of Machine Learning and Cybernetics, April 2020, 11:747–750, doi: https://doi.org/10.1007/s13042-020-01096-5 (24/25/48)

[35]

(2019) Muhammed J. A. Patwary(*), Xi-Zhao Wang, Dasen Yan. Impact of Fuzziness Measures on the Performance of Semi-supervised Learning. International Journal of Fuzzy Systems, July 2019, 21(5): 1430-1442, doi: https://doi.org/10.1007/s40815-019-00666-2 (2/2/6)

[34]

(2018) Xizhao Wang(*), Weipeng Cao. Non-iterative approaches in training feed-forward neural networks and their applications. Soft Computing, June 2018, 22(11):3473–3476, doi: https://doi.org/10.1007/s00500-018-3203-0 (24/25/30)

[33]

(2017) Weipeng Cao, Zhong Ming(*), Xizhao Wang, Shubin Cai. Improved Bidirectional Extreme Learning Machine Based on Enhanced Random Search. Memetic Computing, July 2017, 11(1): 19-26, doi: https://doi.org/10.1007/s12293-017-0238-1 (15/15/20)

[32]

(2017) Weihua Xu(*), Mengmeng Li, Xizhao Wang. Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System. International Journal of Fuzzy Systems, August 2017, 19(4): 1200-1216, doi: https://doi.org/10.1007/s40815-016-0230-9 (35/35/43)

[31]

(2014) Xi-zhao Wang, Abdallah Bashir Musa(*), Advances in neural network based learning, International Journal of Machine Learning and Cybernetics, February 2014, 5(1): 1-2, doi: https://doi.org/10.1007/s13042-013-0220-2 (17/17/15)

[30]

(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)

[29]

(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)

[28]

(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)

[27]

(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)

[26]

(2007) Ng Wing(*), DS Yeung, De-Feng Wang, Eric Tsang, Xizhao Wang. Localized generalization error of Gaussian-based classifiers and visualization of decision boundaries, Soft Computing, February 2007, 11(4): 375-381, doi: https://doi.org/10.1007/s00500-006-0092-4 (7/7/13)

[25]

(2007) DS Yeung, Defeng Wang(*), Ng Wing, Eric Tsang, Xizhao Wang. Structured large margin machines: sensitive to data distribution. Machine Learning, August 2007, 68(2): 171-200, doi: https://doi.org/10.1007/s10994-007-5015-9 (53/62/71)

[24]

(2006) Degang Chen(*), Qiang He, Chunru Dong, Xizhao Wang. A method to construct the mapping to the feature space for the dot product kernels. Lecture Notes in Artificial Intelligence, 2006, 3930: 918-929, doi: https://doi.org/10.1007/11739685_96 (0/0/1)

[23]

(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)

[22]

(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)

[21]

(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)

[20]

(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)

[19]

(2005) Caihong Sun(*), S. C. K. Shiu, Xizhao Wang. Organizing large case library by linear programming. Lecture Notes in Artificial Intelligence, November 2005, 3789: 554-564, doi: https://doi.org/10.1007/11579427_56 (0/0/0)

[18]

(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)

[17]

(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)

[16]

(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)

[15]

(2003) Xizhao Wang(*), Minghua Zhao, Dianhui Wang. Selection of parameters in building fuzzy decision trees. Lecture Notes in Artificial Intelligence, 2003, 2903: 282-292, doi: https://doi.org/10.1007/978-3-540-24581-0_24 (0/0/2)

[14]

(2001) Guoqing Cao(*), Simon Shiu, Xizhao Wang. A fuzzy-rough approach for case base maintenance. Lecture Notes in Artificial Intelligence, 2001, 2080: 118-130, doi: https://doi.org/10.1007/3-540-44593-5_9 (10/10/27)

[13]

(2001) S. C. K. Shiu(*), Caihung Sun, Xizhao Wang, Daniel S. Yeung. Maintaining Case-Based Reasoning systems using fuzzy decision trees. Lecture Notes in Artificial Intelligence, 2001, 1898: 285-296, doi: https://doi.org/10.1007/3-540-44527-7_25 (4/4/40)

[12]

(2019) Hong Zhu, Peng Yao, Xizhao Wang(*). Weight learning from cost matrix in weighted least squares model based on genetic algorithm. International Journal of Bio-Inspired Computation, 2019, 13(4):269–276, doi: https://doi.org/10.1504/IJBIC.2019.100148 (2/2/2)

[11]

(2018) Shi-Xin Zhao(*), Xi-Zhao Wang, Li-Ying Wang, Jun-Mei Hu, Wei-Ping Li. Analysis on fast training speed of extreme learning machine and replacement policy. International Journal of Wireless and Mobile Computing, January 2018, 13(4):314–322, doi: https://doi.org/10.1504/IJWMC.2017.089327 (1/1/1)

[10]

(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)

[9]

(2017) Rana Aamir Raza Ashfaq, Xi-Zhao Wang (*). Impact of fuzziness categorization on divide and conquer strategy for instance selection. Journal of Intelligent and Fuzzy Systems, March 2017, 33(2): 1007-1018, doi: https://doi.org/10.3233/JIFS-162297 (7/7/7)

[8]

(2016) Junhai Zhai(*), Ta Li, Xizhao Wang. A cross-selection instance algorithm, Journal of Intelligent & Fuzzy Systems. February 2016, 30(2): 717–728, doi: https://doi.org/10.3233/IFS-151792 (12/15/17)

[7]

(2015) Xi-zhao Wang(*), Rana Aamir and Ai-Min Fu, Fuzziness based sample categorization for classifier performance improvement, Journal of Intelligent & Fuzzy Systems , June 2015, 29(3): 1185–1196, doi: https://doi.org/10.3233/IFS-151729 (152/154/153)

[6]

(2015)Xi-zhao Wang(*). Learning from big data with uncertainty-editorial. Journal of Intelligent and Fuzzy Systems, October 2015, 28(5): 2329-2330, doi: https://doi.org/10.3233/IFS-141516 (101/101/56)

[5]

(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)

[4]

(2008)Xizhao Wang(*), Shuxia Lu, Junhai Zhai. Fast fuzzy multicategory SVM based on support vector domain description. International Journal of Pattern Recognition and Artificial Intelligence, February 2008, 22(1): 109-120, doi: https://doi.org/10.1142/S0218001408006144 (46/46/51)

[3]

(2007) Shuyuan Jin(*), DS Yeung, Xizhao Wang. Internet anomaly detection based on statistical covariance matrix. International Journal of Pattern Recognition and Artificial Intelligences, May 2007, 21(3): 591-606, doi: https://doi.org/10.1142/S0218001407005557 (0/0/1)

[2]

(2005) ECC Tsang(*), Xizhao Wang. An approach to case-based maintenance: Selecting representative cases. International Journal of Pattern Recognition and Artificial Intelligence, February 2005, 19(1): 79-89, DOI: 10.1142/S0218001405003909 (2/2/5)

[1]

(2001) Simon C. K. Shiu(*), Daniel S. Yeung, Caihung Sun, Xizhao Wang. Transferring case knowledge to adaptation knowledge: An approach for case-base maintenance. Computational Intelligence, May 2001, 17(2): 295-314, doi: https://doi.org/10.1111/0824-7935.00146 (27/30/80)