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  • [105]
    Jianhui Pang, Yanghui Rao(*), Haoran Xie, Xizhao Wang, Fu Lee Wang, Tak-Lam Wong, and Jian Yin; Fast Supervised Topic Models for Short Text Emotion Detection; Submitted to IEEE Transactions on Cybernetics
  • [104]
    Zhi Wang, Xizhao Wang(*), A Deep Stochastic Weight Assignment Network and its Application to Chess Playing; Submitted to Journal of Parallel and Distributed Computing
  • [103]
    Weipeng Cao, Xizhao Wang(*), Zhong Ming, Jinzhu Gao; A Review on Neural Networks with Random Weights; Submitted NeuroComputing
  • [102]
    Hong Zhu, Yichao He, Eric Tsang, Xizhao Wang(*); Discrete Differential Evolution for the Discounted {0-1} Knapsack Problem; Journal of Bio-inspired Computation, Accepted in June 2017
  • [101]
    Wing W. Y. Ng, Jianjun Zhang(*), Witold Pedrycz, Xizhao Wang, Daniel S. Yeung; Incremental Learning for Streaming Imbalanced Classification Problems by Localized Generalization Error-based Ensemble Weighting and Drift Detection; IEEE Transactions on Neural Networks and Learning Systems; Under review
  • [100]
    Changzhong Wang(*); Qinghua Hu; Xi-Zhao Wang; Degang Chen; Yuhua Qian; Feature selection based on neighborhood discrimination index, IEEE Transactions on Neural Networks and Learning Systems; Accepted in May 2017
  • [99]
    Yichao He, Haoran Xie, Tak-Lam Wong, Xizhao Wang (*), A novel binary artificial bee colony algorithm for the set-union knapsack problem, Accepted (May 2017), Future Generation Computer Systems
  • [98]
    Ran Wang, Xi-zhao Wang (*), Sam Kwong, and Chen Xu, Incorporating Diversity and Informativeness in Multiple-Instance Active Learning, Accepted in May 2017; IEEEE Transactions on Fuzzy Systems
  • [97]
    Xizhao Wang, Tianlun Zhang, Ran Wang(*), Non-Iterative Deep Learning: Incorporating Restricted Boltzmann Machine into Multilayer Random Weight Neural Networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Volume: 47 Issue: 8, DOI: 10.1109/TSMC.2017.2701419
  • [96]
    Xizhao Wang, Ran Wang(*), Chen Xu, Discovering the Relationship Between Generalization and Uncertainty By Incorporating Complexity of Classification, Accepted (November 2016), IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2017.2653223
  • [95]
    Rana Aamir Raza Ashfaq, Xi-Zhao Wang (*); Impact of fuzziness categorization on divide and conquer strategy for instance selection; Accepted (March 2017), Journal of Intelligent and Fuzzy Systems xx(20xx)xx-xx). DOI:10.3233/JIFS-162297
  • [94]
    Hongyu Zhu and Xi-Zhao Wang (*); A cost-sensitive semi-supervised learning model based on uncertainty, Neurocomputing,Volume 251, 16 August 2017, Pages 106–114
  • [93]
    Hong Zhu, Eric Tsang, Xizhao Wang, Rana Aamir Raza Ashfaq, Monotonic classification Extreme Learning Machine, NeuroComputing, Volume 225, 15 February 2017, Pages 205–213
  • [92]
    Weipeng Cao, Zhong Ming, Xizhao Wang and Shubin Cai, Improved Bidirectional Extreme Learning Machine Based on Enhanced Random Search, (October 2016) accepted in Memetic Computing
  • [91]
    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, 378 (2017) 484–497(SCI,Web-of-Science:8)
  • [90]
    JinhaiLi, Cherukuri,Aswani Kumar, ChanglinMei, XizhaoWang, Comparison of reduction in formal decision contexts, International Journal of Approximate Reasoning, 2017, 80: 100–122(SCI,Web-of-Science:0)
  • [89]
    Hong-Jie Xing,Xi-Zhao Wang,Selective ensemble of SVDDs with Renyi entropy based diversity measure,Pattern Recognition,January 2017,185-196.(SCI,Web-of-Science:0)
  • [88]
    Junhai Zhai, Xizhao Wang, Xiaohe Pang, Voting-based Instance Selection from Large Data Sets with MapReduce and Random Weight Networks, Information Sciences 367–368 (2016) 1066–1077(SCI,Web-of-Science:1)
  • [87]
    Weihua Xu, Mengmeng Li, Xizhao Wang, Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System, International Journal of Fuzzy Systems, 2016:1-17, DOI 10.1007/s40815-016-0
  • [86]
    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, 2016, 369: 634–647(SCI,Web-of-Science:0)
  • [85]
    Xizhao Wang and Yulin He, Learning from Uncertainty for Big Data (Future Analytical Challenges and Strategies),IEEE Systems, Man, & Cybernetics Magazine, pages 26-31,April issue, 2016(SCI,Web-of-Science:0)
  • [84]
    Junhai Zhai, Ta Li and Xizhao Wang, A cross-selection instance algorithm, DOI:10.3233/IFS-151792, Journal of Intelligent & Fuzzy Systems 30 (2016) 717–728(SCI,Web-of-Science:1)
  • [83]
    Yu-Lin He, Xi-zhao Wang, Joshua Zhexue Huang. Fuzzy nonlinear regression analysis using a random weight network. Information Sciences, 2016, 364-365: 222-240.(SCI,Web-of-Science:10)
  • [82]
    Huanyu Zhao, Zhaowei Dong, Tongliang Li, Xizhao Wang, Chaoyi Pang,Segmenting time series with connected lines under maximum error bound,Information Sciences, 2015, 345:1-8(SCI,Web-of-Science:2)
  • [81]
    Xi-zhao Wang, Rana Aamir and Ai-Min Fu, Fuzziness based sample categorization for classifier performance improvement, Journal of Intelligent & Fuzzy Systems 29 (2015) 1185–1196, DOI:10.3233/IFS-151729 IOS Press(SCI,Web-of-Science:22)
  • [80]
    Xi-zhao Wang, Hong-Jie Xing, Yan Li, et al, A Study on Relationship between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning,IEEE Transactions on Fuzzy Systems, 2015, 23(5): 1638-1654(SCI,Web-of-Science:37)
  • [79]
    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,2015, 42: 21-50(SCI,Web-of-Science:26)
  • [78]
    Yu-lin He, Joshua Zhexue Huang, Xi-zhao Wang, Rana Aamir Raza Ashfaq, Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models, PAKDD 2015, Lecture Notes in Computer Science, 2015, 9077: 405-417(SCI,Web-of-Science:0)
  • [77]
    Ran Wang, Sam Kwon, Xi-zhao Wang, and Qing-Shan Jiang, Segment Based Decision Tree Induction with Continuous Valued Attributes, IEEE Transactions onCybernetics, 2015, 45(7): 1262-1275 (SCI,Web-of-Science:7)
  • [76]
    Xi-zhao Wang and Zhe-Xue Huang, Editorial: Uncertainty in learning from big data, Fuzzy Sets and Systems, 2015, 258: 1-4 (SCI,Web-of-Science:4)
  • [75]
    Xi-zhao Wang, Learning from big data with uncertainty - editorial, Journal of Intelligent and Fuzzy Systems, 2015, 28(5): 2329-2330(SCI,Web-of-Science:16)
  • [74]
    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, 2015, 19(4): 743–760 (SCI,Web-of-Science:8)
  • [73]
    He Y L, Wang R, Kwong S, Wang X Z. Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis. Information Sciences, 2014, 259(3):252-268.(SCI,Web-of-Science:20)
  • [72]
    Xi-zhao Wang,Abdallah Bashir Musa, Advances in neural network based learning,International Journal of Machine Learning and Cybernetics , 2014, (5): 1-2 (SCI,Web-of-Science:4)
  • [71]
    Xi-zhao Wang, Ran Wang, Hui-Min Feng, Huachao Wang, A new approach to classifier fusion based on upper integral, IEEE Transactions on Cybernetics, 2014, 44(5): 620-635 (SCI,Web-of-Science:9)
  • [70]
    Xi-zhao Wang, Yu-Lin He, Dabby D. Wang, Non-Naive Bayesian Classifiers for Classification Problems with Continuous Attributes; IEEE Transactions on Cybernetics, 2014, 44(1): 21-39(SCI,Web-of-Science:26)
  • [69]
    Hui-min Feng and Xi-zhao Wang, Performance Improvement of Classifier Fusion for Batch Samples Based on Upper Integral, Neural Networks, 2015, pp. 87-93 (SCI,Web-of-Science:1)
  • [68]
    Chun-Ru Dong, Wing W.Y. Ng, Xi-zhao Wang, et al, An improved differential evolution and its application to determining feature weights in similarity-based Clustering, Neurocomputing, 2014, 146: 95-103 (SCI,Web-of-Science:3)
  • [67]
    Ai-Min Fu, Xi-zhao Wang, Yu-Lin He, and Lai-Sheng Wang, A study on residence error of training an extreme learning machine and its application to evolutionary algorithms, Neurocomputing, 2014, 146(1): 75-82 (SCI,Web-of-Science:2)
  • [66]
    Hong-Yan Ji, Xi-zhao Wang, Yu-Lin He and Wen-Liang Li, A study on relationships between heuristics and optimal cuts in decision tree induction, Computers and Electrical Engineering, 2014, 40: 1429-1438 (SCI,Web-of-Science:0)
  • [65]
    James N. K. Liu, Yu-Lin He, Edward H. Y. Lim, Xi-zhao Wang, Domain ontology graph model and its application in Chinese text classification, Neural Computing and Applications, 2014, 24(3-4): 779-798(SCI,Web-of-Science:0)
  • [64]
    Xi-zhao Wang and Hui Wang, Guest editorial: learning from uncertainty and its application to intelligent systems of web information, World Wide Web-internetWeb Information Systems, 2014, 17(5): 1027-1028 (SCI,Web-of-Science:0)
  • [63]
    Lisha Hu, Shuxia Lu, Xi-zhao Wang, A New and Informative Active Learning Approach for Support Vector Machine, Information Sciences, 2013, 244: 142-160(SCI,Web-of-Science:2)
  • [62]
    Suyun Zhao, Xi-zhao Wang, Degang Chen and Eric Tsang, Nested structure in parameterized rough reduction, 2013, 248: 130-150 (SCI,Web-of-Science:10)
  • [61]
    Xi-zhao Wang, Qing-Yan Shao, Miao Qing, Jun-Hai Zhai, Architecture selection for networks trained with extreme learning machine using localized generalization error model, Neurocomputing, 2013, 102: 3-9(SCI,Web-of-Science:20)
  • [60]
    Xi-zhao Wang, Ling-Cai Dong, Jian-Hui Yan, Maximum ambiguity based sample selection in fuzzy decision tree induction, IEEE Transactions on Knowledge and Data Engineering, 2012, 24(8): 1491-1505(SCI,Web-of-Science:52)
  • [59]
    Qiang Hua, Li-jie Bai, and Xi-zhao Wang, Local similarity and diversity preserving discriminant projection for face and handwriting digits recognition,NeuroComputing, 86:150-157, Jun. 2012(SCI,Web-of-Science:2)
  • [58]
    Yu-Lin He, James N. K. Liu, Xi-zhao Wang, et al, Optimal bandwidth selection for re-substitution entropy estimation, Applied Mathematics andComputation,2012, 219(8): 3425-3460(SCI,Web-of-Science:1)
  • [57]
    Xi-zhao Wang, Yu-Lin He, Ling-Cai Dong, et al, Particle swarm optimization for determining fuzzy measures from data, Information Sciences, 2011, 181(19): 4230-4252(SCI,Web-of-Science:55)
  • [56]
    Xi-zhao Wang, Ai-Xia Chen, Hui-Min Feng, Upper integral network with extreme learning mechanism, Neurocomputing, 2011, 74(16): 2520-2525(SCI,Web-of-Science:48)
  • [55]
    Su-Yun Zhao, Eric C. C. Tsang, De-Gang Chen, Xi-zhao Wang, Building a rule-based classifier-a fuzzy-rough set approach, IEEE Transactions on Knowledge and Data Engineering, 2010, 22(5): 624-638(SCI,Web-of-Science:41)
  • [54]
    Xi-zhao Wang, Chun-Ru Dong, Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy, IEEE Transactions on Fuzzy Systems, 2009, 17(3): 556-567(SCI,Web-of-Science:104)
  • [53]
    Xi-zhao Wang, Jun-Hai Zhai, Shu-Xia Lu, Induction of multiple fuzzy decision trees based on rough set technique, Information Sciences, 2008,178(16):3188-3202(SCI,Web-of-Science:101)
  • [52]
    Xi-zhao Wang, Chun-Guo Li, A Definition of Partial Derivative of Random Functions and Its Application to RBFNN Sensitivity Analysis, Neurocomputing, 2008, 71(7-9):1515-1526(SCI,Web-of-Science:7)
  • [51]
    Ng Wing, DS. Yeung, M Firth, ECC Tsang, Xi-zhao Wang, Feature Selection Using Localized Generalization Error for Supervised Classification Problems Using RBFNN, Pattern Recognition, 2008,41(12):3706-3719(SCI,Web-of-Science:22)
  • [50]
    Xi-zhao Wang, Jun-Hai Zhai, Su-Fang Zhang, A model of finite-step random walk with absorbent boundaries, International Journal of Computer Mathematics, 2008, 85(11):1685-1696(SCI,Web-of-Science:0)
  • [49]
    Xi-zhao Wang, Shu-Xia Lu, Jun-Hai Zhai, Fast fuzzy multicategory SVM based on support vector domain description, International Journal of Pattern Recognition and Artificial Intelligences, 2008, 22(1):109-120 (SCI,Web-of-Science:25)
  • [48]
    Xi-zhao Wang, Feng Guo, Xiang-Hui 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(SCI,Web-of-Science:31)
  • [47]
    Daniel Yeung, Shu-Yuan Jin, Xi-zhao Wang, Covariance-matrix modeling and detecting various flooding attacks, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2007, 37(2): 157-169(SCI,Web-of-Science:12)
  • [46]
    DS Yeung, Ng Wing, De-feng Wang, Eric Tsang, Xi-zhao Wang, Localized generalization error model and its application to architecture selection for radial basis function neural network, IEEE Transactions on Neural Networks, 2007, 18(5): 1294-1305(SCI,Web-of-Science:
  • [45]
    Xi-zhao Wang, Eric Tsang, Su-Yun Zhao, De-Gang Chen, Daniel Yeung, Learning fuzzy rules from fuzzy examples based on rough set techniques, Information Sciences, 2007, 177(20):4493-4514(SCI,Web-of-Science:92)
  • [44]
    Xi-zhao Wang, Chun-Ru Dong, Tie-Gang Fan, Training T-S norm neural networks to refine weights for fuzzy if-then rules, Neurocomputing, 2007, 70(13-15):2581-2587(SCI,Web-of-Science:20)
  • [43]
    De-gang Chen, Qiang He, Xi-zhao Wang, On Linear Separability of Data Sets in Feature Space, Neurocomputing, 2007, 70(13):2441-2448(SCI,Web-of-Science:11)
  • [42]
    Shu-yuan Jin, DS Yeung, Xi-zhao Wang, Network Intrusion Detection in Covariance Feature Space, Pattern Recognition, 2007, 40(8):2185-2197(SCI,Web-of-Science:15)
  • [41]
    Xi-zhao Wang,Su-Fang Zhang, Jun-Hai Zhai, A nonlinear integral defined on partition and its application to decision trees, Soft Computing, 2007, 11(4):317-321(SCI,Web-of-Science:5)
  • [40]
    Yan Li, Xi-zhao Wang, Ming-Hu Ha, An on-line Multi-CBR agent dispatching algorithm, Soft Computing, 2007, 11(1):1-5(SCI,Web-of-Science:1)
  • [39]
    DS Yeung, De-Feng Wang, Ng Wing, Eric Tsang, Xi-zhao Wang, Structured large margin machines: sensitive to data distribution, Machine Learning, 2007,68(2):171-200(SCI,Web-of-Science:33)
  • [38]
    Ng Wing, DS Yeung, De-Feng Wang, Eric Tsang, Xi-zhao Wang, Localized generalization error of Gaussian-based classifiers and visualization of decisionboundaries, Soft Computing, 2007, 11(4): 375-381(SCI,Web-of-Science:4)
  • [37]
    Ng Wing, DS Yeung, De-Feng Wang, Eric Tsang, Xi-zhao Wang, Localized generalization error of Gaussian-based classifiers and visualization of decisionboundaries, Soft Computing, 2007, 11(4): 375-381(SCI,Web-of-Science:4)
  • [36]
    Shu-Yuan Jin, DS Yeung, Xi-zhao Wang, Internet anomaly detection based on statistical covariance matrix, International Journal of Pattern Recognition and Artificial Intelligences, 2007,21(3):591-606(SCI,Web-of-Science:0)
  • [35]
    Xi-zhao Wang, Jun Shen, Using special structured fuzzy measure to represent interaction among IF-THEN rules, Lecture Notes in Artificial Intelligence, 2006, 3930: 459-466(SCI,Web-of-Science:1)
  • [34]
    Qiang He, Xi-zhao Wang, Jun-Fen Chen, et al, A parallel genetic algorithm for solving the inverse problem of support vector machines, Lecture Notes in Artificial Intelligence, 2006, 3930: 871-879(SCI,Web-of-Science:1)
  • [33]
    John W. T. Lee, Xi-zhao Wang, Jin-Feng Wang, Reduction of attributes in ordinal decision systems, Lecture Notes in Artificial Intelligence, 2006, 3930: 578-587(SCI,Web-of-Science:0)
  • [32]
    Shu-Yuan Jin, DS Yeung, Xi-zhao Wang, et al, A covariance matrix based approach to Internet anomaly detection, Lecture Notes in Artificial Intelligence, 2006, 3930: 691-700 (SCI,Web-of-Science:0)
  • [31]
    De-Gang Chen, Qiang He, Chun-Ru Dong, Xi-zhao 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(SCI,Web-of-Science:0)
  • [30]
    DS Yeung, De-Gang Chen, ECC Tsang, JWT Lee, Xi-zhao Wang, On the generalization of fuzzy rough sets, IEEE Transactions on Fuzzy Systems, 2005, 13(3): 343-361(SCI,Web-of-Science:162)
  • [29]
    Xi-zhao Wang, Qiang He, De-Gang Chen, Daniel Yeung, A genetic algorithm for solving the inverse problem of support vector machines, Neurocomputing, 2005, 68:225-238(SCI,Web-of-Science:31)
  • [28]
    De-Gang Chen, ECC Tsang, DS Yeung, Xi-zhao Wang, The parameterization reduction of soft sets and its applications, Computers & Mathematics with Applications, 2005,49(5-6): 757-763(SCI,Web-of-Science:209)
  • [27]
    Xi-zhao Wang, Chun-Guo Li, A new definition of sensitivity for RBFNN and its applications to feature reduction, Lecture Notes in Computer Science, 2005, 3496:81-86(SCI,Web-of-Science:9)
  • [26]
    De-Gang Chen, Qiang He, Xi-zhao Wang, The infinite polynomial kernel for support vector machine, Lecture Notes in Artificial Intelligence, 2005, 3584: 267-275(SCI,Web-of-Science:2)
  • [25]
    Cai-Hong Sun, S. C. K. Shiu, Xi-zhao Wang, Organizing large case library by linear programming, Lecture Notes in Artificial Intelligence, 2005, 3789: 554-564(SCI,Web-of-Science:0)
  • [24]
    ECC Tsang, Xi-zhao Wang, An approach to case-based maintenance: Selecting representative cases, International Journal of Pattern Recognition and Artificial Intelligence, 2005,19(1):79-89(SCI,Web-of-Science:2)
  • [23]
    DS Yeung, Xi-zhao Wang, ECC Tsang, Handling interaction in fuzzy production rule reasoning, IEEE Transactions on Systems, Man, and Cybernetics, Part B-Cybernetics, 2004, 34(5): 1979-1987(SCI,Web-of-Science:8)
  • [22]
    ECC Tsang, DS Yeung, JWT Lee, DM Huang, Xi-zhao Wang, Refinement of generated fuzzy production rules by using a fuzzy neural network, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2004, 34(1): 409-418(SCI,Web-of-Science:12)
  • [21]
    Xi-zhao Wang, Ya-Dong Wang, Li-Juan Wang, Improving fuzzy c-means clustering based on feature-weight learning, Pattern Recognition Letters, 2004, 25(10):1123-1132(SCI,Web-of-Science:146)
  • [20]
    Xi-zhao Wang, Qiang He, Enhancing generalization capability of SVM classifiers with feature weight adjustment, Lecture Notes in Computer Science, 2004, 3213:1037-1043(SCI,Web-of-Science:7)
  • [19]
    ECC Tsang, DS Yeung, Xi-zhao Wang, OFFSS: Optimal fuzzy-valued feature subset selection, IEEE Transactions on Fuzzy Systems, 2003, 11(2): 202-213(SCI,Web-of-Science:31)
  • [18]
    Ming-Hu Ha, Xi-zhao Wang, Lan-Zhen Yang, et al, Sequences of (S) fuzzy integrable functions, Fuzzy Sets and Systems, 2003, 138 (3): 507-522(SCI,Web-of-Science:5)
  • [17]
    Xi-zhao Wang, Ming-Hua Zhao, Dian-Hui Wang, Selection of parameters in building fuzzy decision trees, Lecture Notes in Artificial Intelligence, 2003, 2903: 282-292(SCI,Web-of-Science:0)
  • [16]
    DS Yeung, Xi-zhao Wang, Improving performance of similarity-based clustering by feature weight learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(4): 556-561(SCI,Web-of-Science:57)
  • [15]
    Xi-zhao 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, 2001, 31(2): 215-226(SCI,Web-of-Science:64)
  • [14]
    Xi-zhao Wang, Zi-Mian Zhong, Ming-Hu Ha, Iteration algorithms for solving a system of fuzzy linear equations, Fuzzy Sets and Systems, 2001, 119(1):121-128(SCI,Web-of-Science:37)
  • [13]
    Xi-zhao Wang, Ya-Dong Wang, X F Xu, et al, A new approach to fuzzy rule generation: fuzzy extension matrix, Fuzzy Sets and Systems, 2001, 123(3): 291-306(SCI,Web-of-Science:31)
  • [12]
    S. C. K. Shiu, Cai-Hung Sun, Xi-zhao Wang, et al, Maintaining Case-Based Reasoning systems using fuzzy decision trees, Lecture Notes in Artificial Intelligence, 2001, 1898: 285-296(SCI,Web-of-Science:0)
  • [11]
    Guo-Qing Cao, Simon Shiu, Xi-zhao Wang, A fuzzy-rough approach for case base maintenance, Lecture Notes in Artificial Intelligence, 2001, 2080: 118-130(SCI,Web-of-Science:6)
  • [10]
    Simon C. K. Shiu, Daniel S. Yeung, Cai-Hung Sun, Xi-zhao Wang, Transferring case knowledge to adaptation knowledge: An approach for case-base maintenance, Computational Intelligence, 2001, 17(2): 295-314(SCI,Web-of-Science:26)
  • [9]
    ECC Tsang, Xi-zhao Wang, DS Yeung, Improving learning accuracy of fuzzy decision trees by hybrid neural networks, IEEE Transactions on Fuzzy Systems,2000, 8(5): 601-614(SCI,Web-of-Science:50)
  • [8]
    Xi-zhao Wang, Bin Chen, Guo-Liang Qian, et al, On the optimization of fuzzy decision trees, Fuzzy Sets and Systems, 2000,112(1):117-125(SCI,Web-of-Science:86)
  • [7]
    Xi-zhao Wang, Jia-Rong Hong, Learning optimization in simplifying fuzzy rules, Fuzzy Sets and Systems, 1999,106(3):349-356(SCI,Web-of-Science:38)
  • [6]
    Xi-zhao Wang, Jia-Rong Hong, On the handling of fuzziness for continuous-valued attributes in decision tree generation, Fuzzy Sets and Systems, 1998,99(3):283-290(SCI,Web-of-Science:15)
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