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2020 – today
- 2024
[j79]Chengling Zhang, Eric C. C. Tsang, Weihua Xu, Yidong Lin, Lanzhen Yang, Jiaming Wu:
Dynamic updating variable precision three-way concept method based on two-way concept-cognitive learning in fuzzy formal contexts. Inf. Sci. 655: 119818 (2024)- [j78]Jiaming Wu
, Eric C. C. Tsang, Weihua Xu, Chengling Zhang, Lanzhen Yang:
Correlation concept-cognitive learning model for multi-label classification. Knowl. Based Syst. 290: 111566 (2024) - 2023
- [j77]Lanzhen Yang, Eric C. C. Tsang, Xizhao Wang, Chengling Zhang:
ELM parameter estimation in view of maximum likelihood. Neurocomputing 557: 126704 (2023) - [j76]Cheng-Ling Zhang, Eric C. C. Tsang, Weihua Xu, Yidong Lin, Lanzhen Yang:
Incremental concept-cognitive learning approach for concept classification oriented to weighted fuzzy concepts. Knowl. Based Syst. 260: 110093 (2023) - [j75]Meng Hu, Yanting Guo, Degang Chen, Eric C. C. Tsang, Qingshuo Zhang:
Attribute reduction based on neighborhood constrained fuzzy rough sets. Knowl. Based Syst. 274: 110632 (2023) - [j74]Qingshuo Zhang, Eric C. C. Tsang, Qiang He, Yanting Guo:
Ensemble of kernel extreme learning machine based elimination optimization for multi-label classification. Knowl. Based Syst. 278: 110817 (2023) - [j73]Qingshuo Zhang, Eric C. C. Tsang, Qiang He, Meng Hu:
Distance metric learning with local multiple kernel embedding. Int. J. Mach. Learn. Cybern. 14(1): 79-92 (2023) - [c61]Yanting Guo, Meng Hu, Qiang Liu, Eric C. C. Tsang, Xizhao Wang:
Local Weighted Neighborhood Rough Sets for Weakly Labeled Data. ICMLC 2023: 147-152 - 2022
- [j72]Meng Hu, Eric C. C. Tsang, Yanting Guo, Degang Chen, Weihua Xu:
Attribute reduction based on overlap degree and k-nearest-neighbor rough sets in decision information systems. Inf. Sci. 584: 301-324 (2022) - [j71]Yanting Guo, Meng Hu, Xizhao Wang, Eric C. C. Tsang, Degang Chen, Weihua Xu:
A robust approach to attribute reduction based on double fuzzy consistency measure. Knowl. Based Syst. 253: 109585 (2022) - [j70]Meng Hu, Eric C. C. Tsang, Yanting Guo, Qingshuo Zhang, Degang Chen, Weihua Xu:
A novel approach to concept-cognitive learning in interval-valued formal contexts: a granular computing viewpoint. Int. J. Mach. Learn. Cybern. 13(4): 1049-1064 (2022) - [j69]Meng Hu, Eric C. C. Tsang, Yanting Guo, Weihua Xu:
Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems. IEEE Trans. Cybern. 52(6): 5559-5572 (2022) - 2021
- [j68]Patrick P. K. Chan, Juan Zheng, Han Liu, Eric C. C. Tsang, Daniel S. Yeung:
Robustness analysis of classical and fuzzy decision trees under adversarial evasion attack. Appl. Soft Comput. 107: 107311 (2021) - [j67]Meng Hu, Eric C. C. Tsang, Yanting Guo, Degang Chen, Weihua Xu:
A novel approach to attribute reduction based on weighted neighborhood rough sets. Knowl. Based Syst. 220: 106908 (2021) - [j66]Patrick P. K. Chan, Zhi-Min He, Xian Hu, Eric C. C. Tsang, Daniel S. Yeung, Wing W. Y. Ng:
Causative label flip attack detection with data complexity measures. Int. J. Mach. Learn. Cybern. 12(1): 103-116 (2021) - [c60]Bingjiao Fan, Guo-Cheng Li, Eric C. C. Tsang, Wentao Li:
Rule Acquisition Based on Multi-Level Cognitive Learning in Multi-Decision Data. ICMLC 2021: 1-6 - [c59]Meng Hu, Eric C. C. Tsang, Yanting Guo, Qingshuo Zhang:
An Improved ${k}$-Means Algorithm with Spatial Constraints for Image Segmentation. ICMLC 2021: 1-7 - [c58]Wentao Li, Shi-Qi Zeng, Tao Zhan, Bingjiao Fan, Eric C. C. Tsang:
Double-Quantitative-Based Knowledge Reduction Approach to Inconsistency Information System. ICMLC 2021: 1-6 - [c57]Lanzhen Yang, Eric C. C. Tsang, Xi-Zhao Wang:
An Object-Induced Fuzzy Three-Way Concept Lattice Analysis Based on Two Thresholds. ICMLC 2021: 1-6 - [c56]Qingshuo Zhang, Eric C. C. Tsang, Meng Hu, Qiang He, Degang Chen:
Fuzzt Set-Based Kernel Extreme Learning Machine Autoencoder for Multi-Label Classification. ICMLC 2021: 1-6 - [c55]Cheng-Ling Zhang, Eric C. C. Tsang, Wei-Hua Xu, Yidong Lin:
A Matrix-Based Granular Reduct Approach in Formal Contexts. ICMLC 2021: 1-6 - [c54]Da-Sheng Zhao, Jingjing Song, Tai-Hua Xu, Eric C. C. Tsang:
Accelerator on Multi-Granularity Attribute Reduction for Continuous Parameters. ICMLC 2021: 1-6 - 2020
- [j65]Peng Ni, Suyun Zhao, Xizhao Wang, Hong Chen, Cuiping Li, Eric C. C. Tsang:
Incremental feature selection based on fuzzy rough sets. Inf. Sci. 536: 185-204 (2020) - [j64]Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen:
Adaptive weighted generalized multi-granulation interval-valued decision-theoretic rough sets. Knowl. Based Syst. 187 (2020) - [j63]Yanting Guo, Eric C. C. Tsang, Meng Hu, Xuxin Lin, Degang Chen, Weihua Xu, Binbin Sang:
Incremental updating approximations for double-quantitative decision-theoretic rough sets with the variation of objects. Knowl. Based Syst. 189 (2020) - [j62]Eric C. C. Tsang, Bingjiao Fan, Degang Chen, Weihua Xu, Wentao Li:
Multi-level cognitive concept learning method oriented to data sets with fuzziness: a perspective from features. Soft Comput. 24(5): 3753-3770 (2020) - [c53]Meng Hu, Eric C. C. Tsang, Yanting Guo, Weihua Xu, Degang Chen:
A Fast Reduction Algorithm with Attribute Pre-Sort Based on Neighborhood Rough Set. ICMLC 2020: 279-284 - [c52]Jingjing Song, Zehua Jiang, Huili Dou, Eric C. C. Tsang:
Supervised Neighborhood Based Ensemble Attribute Reduction. ICMLC 2020: 285-290
2010 – 2019
- 2019
- [j61]Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen:
Local logical disjunction double-quantitative rough sets. Inf. Sci. 500: 87-112 (2019) - [j60]Eric C. C. Tsang, Jingjing Song, Degang Chen, Xibei Yang:
Order based hierarchies on hesitant fuzzy approximation space. Int. J. Mach. Learn. Cybern. 10(6): 1407-1422 (2019) - [j59]Bingjiao Fan, Eric C. C. Tsang, Weihua Xu, Degang Chen, Wentao Li:
Attribute-oriented cognitive concept learning strategy: a multi-level method. Int. J. Mach. Learn. Cybern. 10(9): 2421-2437 (2019) - 2018
- [j58]Hong Zhu, Eric C. C. Tsang, Jie Zhu:
Training an extreme learning machine by localized generalization error model. Soft Comput. 22(11): 3477-3485 (2018) - [c51]Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen:
Logical Disjunction Double-Quantitative Fuzzy Rough Sets. ICMLC 2018: 415-421 - 2017
- [j57]Chenxia Jin, Fachao Li, Eric C. C. Tsang, Larissa Bulysheva, Mikhail Yu. Kataev:
A new compound arithmetic crossover-based genetic algorithm for constrained optimisation in enterprise systems. Enterp. Inf. Syst. 11(1) (2017) - [j56]Yanyan Yang, Degang Chen, Hui Wang, Eric C. C. Tsang, Deli Zhang:
Fuzzy rough set based incremental attribute reduction from dynamic data with sample arriving. Fuzzy Sets Syst. 312: 66-86 (2017) - [j55]Hong Zhu, Yi-Chao He, Xizhao Wang, Eric C. C. Tsang:
Discrete differential evolutions for the discounted {0-1} knapsack problem. Int. J. Bio Inspired Comput. 10(4): 219-238 (2017) - [j54]Hong Zhu, Eric C. C. Tsang, Xi-Zhao Wang, Rana Aamir Raza Ashfaq:
Monotonic classification extreme learning machine. Neurocomputing 225: 205-213 (2017) - [j53]Patrick P. K. Chan, Zhe Lin, Xian Hu, Eric C. C. Tsang, Daniel S. Yeung:
Sensitivity based robust learning for stacked autoencoder against evasion attack. Neurocomputing 267: 572-580 (2017) - [j52]Xiaoxia Zhang, Degang Chen, Eric C. C. Tsang:
Generalized dominance rough set models for the dominance intuitionistic fuzzy information systems. Inf. Sci. 378: 1-25 (2017) - [j51]Bingjiao Fan, Eric C. C. Tsang, Weihua Xu, Jianhang Yu:
Double-quantitative rough fuzzy set based decisions: A logical operations method. Inf. Sci. 378: 264-281 (2017) - [j50]Chen Hao, Jinhai Li, Min Fan, Wenqi Liu, Eric C. C. Tsang:
Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions. Inf. Sci. 415: 213-232 (2017) - [j49]Jingjing Song, Eric C. C. Tsang, Degang Chen, Xibei Yang:
Minimal decision cost reduct in fuzzy decision-theoretic rough set model. Knowl. Based Syst. 126: 104-112 (2017) - [j48]Eric C. C. Tsang, Bingzhen Sun, Weimin Ma:
General relation-based variable precision rough fuzzy set. Int. J. Mach. Learn. Cybern. 8(3): 891-901 (2017) - [c50]Yanting Guo, Eric C. C. Tsang, Weihua Xu:
A weighted multi-granulation decision-theoretic approach to multi-source decision systems. ICMLC 2017: 202-210 - [c49]Eric C. C. Tsang, Fan Xingqi, Xuefeng Li, Suyun Zhao:
Weights based ranked fuzzy rough reduction. ICMLC 2017: 223-229 - 2016
- [j47]Suping Xu, Xibei Yang, Hualong Yu, Dong-Jun Yu, Jingyu Yang, Eric C. C. Tsang:
Multi-label learning with label-specific feature reduction. Knowl. Based Syst. 104: 52-61 (2016) - [j46]Eric C. C. Tsang, Qinghua Hu, Degang Chen:
Feature and instance reduction for PNN classifiers based on fuzzy rough sets. Int. J. Mach. Learn. Cybern. 7(1): 1-11 (2016) - [j45]Shuang An, Qinghua Hu, Witold Pedrycz, Pengfei Zhu, Eric C. C. Tsang:
Data-Distribution-Aware Fuzzy Rough Set Model and its Application to Robust Classification. IEEE Trans. Cybern. 46(12): 3073-3085 (2016) - [c48]Eric C. C. Tsang, Su-Yun Zhao:
Random analysis of statistical rough set. ICMLC 2016: 43-47 - [c47]Jingjing Song, Eric C. C. Tsang, Degang Chen, Xibei Yang:
Minimum decision cost reduct for fuzzy decision-theoretic rough set model. ICMLC 2016: 213-218 - [c46]Suping Xu, Xibei Yang, Eric C. C. Tsang, Eric Appiah Mantey:
Neighborhood collaborative classifiers. ICMLC 2016: 470-476 - 2015
- [c45]Eric C. C. Tsang, Jing-Duo Jie, Chen-Xia Jin:
A method to fuzzy multi-objective problems under random environment. ICMLC 2015: 725-730 - [c44]Eric C. C. Tsang, Changzhong Wang, Yang Du, Qiang He:
Basic properties of fuzzy approximation operators under consistent functions. ICMLC 2015: 748-752 - [c43]Eric C. C. Tsang, Suyun Zhao:
The comparative study of fuzzy rough reduction. ICMLC 2015: 753-758 - 2014
- [c42]Qin Qing, Eric C. C. Tsang:
Face Recognition Using Genetic Algorithm. ICMLC (CCIS volume) 2014: 136-143 - [c41]Eric C. C. Tsang, Suyun Zhao:
A Fast Algorithm to Building a Fuzzy Rough Classifier. ICMLC (CCIS volume) 2014: 409-417 - [c40]Eric C. C. Tsang, Changzhong Wang, Du Yan, Jiaze Li:
Neighbourhood-assignment attribute reduction based on general binary relations. ICMLC 2014: 801-806 - 2013
- [j44]Suyun Zhao, Xizhao Wang, Degang Chen, Eric C. C. Tsang:
Nested structure in parameterized rough reduction. Inf. Sci. 248: 130-150 (2013) - [j43]Eric C. C. Tsang, Changzhong Wang, Degang Chen, Congxin Wu, Qinghua Hu:
Communication Between Information Systems Using Fuzzy Rough Sets. IEEE Trans. Fuzzy Syst. 21(3): 527-540 (2013) - [c39]Eric C. C. Tsang, Ming-Wen Shao:
Attribute reduction and attribute characteristics of formal contexts. ICMLC 2013: 124-129 - [c38]Eric C. C. Tsang, Bingzhen Sun:
Generalized variable precision probabilistic rough set. ICMLC 2013: 670-675 - [c37]Eric C. C. Tsang, Suyun Zhao:
The topological structure in parameterized rough sets. ICMLC 2013: 687-692 - 2012
- [c36]Eric C. C. Tsang, Weimin Ma, Bingzhen Sun:
Variable precision rough fuzzy set model based on general relations. ICMLC 2012: 195-199 - [c35]Eric C. C. Tsang, Chen-Xia Jin, Degang Chen, Fa-Chao Li:
An attribute reduction method based on core samples set. ICMLC 2012: 200-205 - [c34]Eric C. C. Tsang, S. Y. Zhao:
Attribute reduction based on interval valued fuzzy granules. ICMLC 2012: 206-211 - 2011
- [c33]Eric C. C. Tsang, Suyun Zhao, Cai-Li Zhou:
A property of reductions in Fuzzy Variable Precision Rough Set model. ICMLC 2011: 160-165 - 2010
- [j42]Suyun Zhao, Eric C. C. Tsang, Degang Chen, Xizhao Wang:
Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach. IEEE Trans. Knowl. Data Eng. 22(5): 624-638 (2010) - [j41]Eric C. C. Tsang, Suyun Zhao:
Decision Table Reduction in KDD: Fuzzy Rough Based Approach. Trans. Rough Sets 11: 177-188 (2010) - [c32]Degang Chen, Xiao Zhang, Eric C. C. Tsang, Yongping Yang:
Sample selection with rough set. ICMLC 2010: 291-295 - [c31]Eric C. C. Tsang, Degang Chen:
On the fuzzy generalization of the Dempster-Shafer theory of evidence. ICMLC 2010: 587-591
2000 – 2009
- 2009
- [j40]Suyun Zhao, Eric C. C. Tsang, Degang Chen:
The Model of Fuzzy Variable Precision Rough Sets. IEEE Trans. Fuzzy Syst. 17(2): 451-467 (2009) - 2008
- [j39]Eric C. C. Tsang, Degang Chen, Daniel S. Yeung:
Approximations and reducts with covering generalized rough sets. Comput. Math. Appl. 56(1): 279-289 (2008) - [j38]Wing W. Y. Ng, Daniel S. Yeung, Eric C. C. Tsang:
The Localized Generalization Error Model for Single Layer Perceptron Neural Network and Sigmoid Support Vector Machine. Int. J. Pattern Recognit. Artif. Intell. 22(1): 121-135 (2008) - [j37]Aki P. F. Chan, Patrick P. K. Chan, Wing W. Y. Ng, Eric C. C. Tsang, Daniel S. Yeung:
A Novel Feature Grouping Method for Ensemble Neural Network Using Localized Generalization Error Model. Int. J. Pattern Recognit. Artif. Intell. 22(1): 137-151 (2008) - [j36]Suyun Zhao, Eric C. C. Tsang:
On fuzzy approximation operators in attribute reduction with fuzzy rough sets. Inf. Sci. 178(16): 3163-3176 (2008) - [j35]Wing W. Y. Ng, Daniel S. Yeung, Michael Firth, Eric C. C. Tsang, Xizhao Wang:
Feature selection using localized generalization error for supervised classification problems using RBFNN. Pattern Recognit. 41(12): 3706-3719 (2008) - [j34]Eric C. C. Tsang, Degang Chen, Daniel S. Yeung, Xizhao Wang, John W. T. Lee:
Attributes Reduction Using Fuzzy Rough Sets. IEEE Trans. Fuzzy Syst. 16(5): 1130-1141 (2008) - [j33]Bo Liu, Zhifeng Hao, Eric C. C. Tsang:
Nesting One-Against-One Algorithm Based on SVMs for Pattern Classification. IEEE Trans. Neural Networks 19(12): 2044-2052 (2008) - [p1]Eric C. C. Tsang, Qingcai Chen, Suyun Zhao, Daniel S. Yeung, Xizhao Wang:
Hybridization of Fuzzy and Rough Sets: Present and Future. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 2008: 45-64 - 2007
- [j32]Eric C. C. Tsang, S. S. Qiu, Daniel S. Yeung:
Stability analysis of a discrete Hopfield neural network with delay. Neurocomputing 70(13-15): 2598-2602 (2007) - [j31]Eric C. C. Tsang, S. S. Qiu, Daniel S. Yeung:
Convergence Analysis of a Discrete Hopfield Neural Network with Delay and its Application to Knowledge Refinement. Int. J. Pattern Recognit. Artif. Intell. 21(3): 515-541 (2007) - [j30]Xizhao Wang, Eric C. C. Tsang, Suyun Zhao, Degang Chen, Daniel S. Yeung:
Learning fuzzy rules from fuzzy samples based on rough set technique. Inf. Sci. 177(20): 4493-4514 (2007) - [j29]Daniel S. Yeung, Defeng Wang, Wing W. Y. Ng, Eric C. C. Tsang, Xizhao Wang:
Structured large margin machines: sensitive to data distributions. Mach. Learn. 68(2): 171-200 (2007) - [j28]Defeng Wang, Lin Shi, Daniel S. Yeung, Eric C. C. Tsang, Pheng-Ann Heng:
Ellipsoidal support vector clustering for functional MRI analysis. Pattern Recognit. 40(10): 2685-2695 (2007) - [j27]Wing W. Y. Ng, Daniel S. Yeung, Defeng Wang, Eric C. C. Tsang, Xizhao Wang:
Localized Generalization Error of Gaussian-based Classifiers and Visualization of Decision Boundaries. Soft Comput. 11(4): 375-381 (2007) - [j26]Daniel S. Yeung, Wing W. Y. Ng, Defeng Wang, Eric C. C. Tsang, Xizhao Wang:
Localized Generalization Error Model and Its Application to Architecture Selection for Radial Basis Function Neural Network. IEEE Trans. Neural Networks 18(5): 1294-1305 (2007) - [j25]Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang:
Weighted Mahalanobis Distance Kernels for Support Vector Machines. IEEE Trans. Neural Networks 18(5): 1453-1462 (2007) - [c30]Degang Chen, Eric C. C. Tsang, Suyun Zhao:
An approach of attributes reduction based on fuzzy TL rough sets. SMC 2007: 486-491 - [c29]Patrick P. K. Chan, Xiaoqin Zeng, Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee:
Neural network ensemble pruning using sensitivity measure in web applications. SMC 2007: 3051-3056 - [c28]Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang:
Sample Reduction for SVMs via Data Structure Analysis. SoSE 2007: 1-6 - 2006
- [j24]Degang Chen, Wenxiu Zhang, Daniel S. Yeung, Eric C. C. Tsang:
Rough approximations on a complete completely distributive lattice with applications to generalized rough sets. Inf. Sci. 176(13): 1829-1848 (2006) - [j23]Zhi-Qiang Liu, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang, John W. T. Lee:
Preface for the special issue: soft computing in machine learning and cybernetics in the journal Soft Computing. Soft Comput. 10(1): 1 (2006) - [j22]John W. T. Lee, Daniel S. Yeung, Eric C. C. Tsang:
Rough sets and ordinal reducts. Soft Comput. 10(1): 27-33 (2006) - [j21]Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang:
Structured One-Class Classification. IEEE Trans. Syst. Man Cybern. Part B 36(6): 1283-1295 (2006) - [c27]Patrick P. K. Chan, Defeng Wang, Eric C. C. Tsang, Daniel S. Yeung:
Structured Large Margin Machine Ensemble. SMC 2006: 840-844 - [c26]Aki P. F. Chan, Wing W. Y. Ng, Daniel S. Yeung, Eric C. C. Tsang, Michael Firth:
Bankruptcy Prediction Using Multiple Classifier System with Mutual Information Feature Grouping. SMC 2006: 845-850 - [c25]Eric C. C. Tsang, Degang Chen, Suyun Zhao, Qiang He:
A Discussion of Attribute Reduction in Fuzzy Rough Sets Using Support Vector Machine. SMC 2006: 3436-3440 - 2005
- [j20]Degang Chen, Jiashang Jiang, Congxin Wu, Eric C. C. Tsang:
Some notes on equivalent fuzzy sets and fuzzy subgroups. Fuzzy Sets Syst. 152(2): 403-409 (2005) - [j19]Eric C. C. Tsang, Xizhao Wang:
An Approach To Case-Based Maintenance: Selecting Representative Cases. Int. J. Pattern Recognit. Artif. Intell. 19(1): 79-89 (2005) - [j18]John W. T. Lee, Daniel S. Yeung, Eric C. C. Tsang:
Hierarchical clustering based on ordinal consistency. Pattern Recognit. 38(11): 1913-1925 (2005) - [j17]Daniel S. Yeung, Degang Chen, Eric C. C. Tsang, John W. T. Lee, Xizhao Wang:
On the generalization of fuzzy rough sets. IEEE Trans. Fuzzy Syst. 13(3): 343-361 (2005) - [j16]Qiwen Ran, Daniel S. Yeung, Eric C. C. Tsang, Qi Wang:
General multifractional Fourier transform method based on the generalized permutation matrix group. IEEE Trans. Signal Process. 53(1): 83-98 (2005) - [c24]Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang, Lin Shi:
Gene Selection Through Sensitivity Analysis of Support Vector Machines. CompLife 2005: 117-127 - [c23]Dongmei Huang, Minghu Ha, Ya-min Li, Eric C. C. Tsang:
Refinement of Fuzzy Production Rules by Using a Fuzzy-Neural Approach. ICMLC 2005: 517-527 - [c22]Eric C. C. Tsang, Suyun Zhao, Daniel S. Yeung, John W. T. Lee:
Learning from an Incomplete Information System with Continuous-Valued Attributes by a Rough Set Technique. ICMLC 2005: 568-577 - [c21]Degang Chen, Eric C. C. Tsang:
On the Local Reduction of Information System. ICMLC 2005: 588-594 - [c20]Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang, Wing W. Y. Ng:
Empirical Study on Fusion Methods Using Ensemble of RBFNN for Network Intrusion Detection. ICMLC 2005: 682-690 - [c19]Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang:
A Covariance Matrix Based Approach to Internet Anomaly Detection. ICMLC 2005: 691-700 - [c18]Wing W. Y. Ng, Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang:
Construction of High Precision RBFNN with Low False Alarm for Detecting Flooding Based Denial of Service Attacks Using Stochastic Sensitivity Measure. ICMLC 2005: 851-860 - [c17]Aki P. F. Chan, Wing W. Y. Ng, Daniel S. Yeung, Eric C. C. Tsang:
Multiple Classifier System with Feature Grouping for Intrusion Detection: Mutual Information Approach. KES (3) 2005: 141-148 - [c16]Defeng Wang, Lin Shi, Daniel S. Yeung, Pheng-Ann Heng, Tien-Tsin Wong, Eric C. C. Tsang:
Support Vector Clustering for Brain Activation Detection. MICCAI 2005: 572-579 - [c15]Wing W. Y. Ng, Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang:
Quantitative study on the generalization error of multiple classifier systems. SMC 2005: 889-894 - [c14]Eric C. C. Tsang, Aki P. F. Chan, Daniel S. Yeung, S. S. Qiu:
Stability Analysis of Discrete Hopfield Neural Networks With Delay and Its Application. SMC 2005: 1017-1023 - [c13]Gloria C. Y. Tsang, Degang Chen, Eric C. C. Tsang, John W. T. Lee, Daniel S. Yeung:
On attributes reduction with fuzzy rough sets. SMC 2005: 2775-2780 - [c12]Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang:
A feature space analysis for anomaly detection. SMC 2005: 3599-3603 - 2004
- [j15]Guoliang Qian, Daniel S. Yeung, Eric C. C. Tsang, Wenhao Shu:
Feature Selection For Chinese Character Recognition Based On Inductive Learning. Int. J. Pattern Recognit. Artif. Intell. 18(8): 1453-1471 (2004) - [j14]Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee, D. M. Huang, X. Z. Wang:
Refinement of generated fuzzy production rules by using a fuzzy neural network. IEEE Trans. Syst. Man Cybern. Part B 34(1): 409-418 (2004) - [j13]Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang:
Handling interaction in fuzzy production rule reasoning. IEEE Trans. Syst. Man Cybern. Part B 34(5): 1979-1987 (2004) - 2003
- [j12]Daniel S. Yeung, Hank-Shun Fong, Eric C. C. Tsang, Wenhao Shu, Xiaolong Wang:
An Approach To Natural Stroke Extraction For Off-Line Loosely-Constrained Handwritten Chinese Characters. Int. J. Pattern Recognit. Artif. Intell. 17(8): 1483-1513 (2003) - [j11]Eric C. C. Tsang, Daniel S. Yeung, Xizhao Wang:
OFFSS: optimal fuzzy-valued feature subset selection. IEEE Trans. Fuzzy Syst. 11(2): 202-213 (2003) - [c11]Eric C. C. Tsang, Xi-Zhao Wang:
Selecting representative cases by generalization capability. SMC 2003: 2617-2622 - 2002
- [j10]John Wan Tung Lee, Daniel S. Yeung, Eric C. C. Tsang:
Ordinal fuzzy sets. IEEE Trans. Fuzzy Syst. 10(6): 767-778 (2002) - [j9]Eric C. C. Tsang, John W. T. Lee, Daniel S. Yeung:
Tuning certainty factor and local weight of fuzzy production rules by using fuzzy neural network. IEEE Trans. Syst. Man Cybern. Part B 32(1): 91-98 (2002) - 2001
- [j8]Daniel S. Yeung, Shenshan Qiu, Eric C. C. Tsang, Xizhao Wang:
A General Updating Rule for Discrete Hopfield-Type Neural Network with Time-Delay and the Corresponding Search Algorithm. Int. J. Comput. Intell. Appl. 1(4): 399-412 (2001) - [j7]Xizhao Wang, Daniel S. Yeung, Eric C. C. Tsang:
A comparative study on heuristic algorithms for generating fuzzy decision trees. IEEE Trans. Syst. Man Cybern. Part B 31(2): 215-226 (2001) - [c10]Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung, Xizhao Wang:
A General Updating Rule for Discrete Hopfield-Type Neural Network with Delay. IJCAI 2001: 789-796 - [c9]Eric C. C. Tsang, Daniel S. Yeung, Xi-Zhao Wang:
Learning weights of fuzzy production rules by a max-min neural network. SMC 2001: 1485-1490 - 2000
- [j6]Eric C. C. Tsang, Xizhao Wang, Daniel S. Yeung:
Improving learning accuracy of fuzzy decision trees by hybrid neural networks. IEEE Trans. Fuzzy Syst. 8(5): 601-614 (2000) - [c8]Eric C. C. Tsang, Shenshan Qiu, Daniel S. Yeung:
Refinement of fuzzy production rules by neuro-fuzzy networks. SMC 2000: 200-205 - [c7]Eric C. C. Tsang, Hongbing Li, Daniel S. Yeung, John W. T. Lee:
Fuzzy weighted classification rules induction from data. SMC 2000: 230-235 - [c6]Yue Joyce Shu, Eric C. C. Tsang, Daniel S. Yeung, Daming Shi:
Mining fuzzy association rules with weighted items. SMC 2000: 1906-1911 - [c5]Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung:
Stability of discrete Hopfield neural networks with time-delay. SMC 2000: 2545-2550
1990 – 1999
- 1999
- [j5]Daniel S. Yeung, Simon C. K. Shiu, Eric C. C. Tsang:
Modelling flexible manufacturing systems using weighted Fuzzy Coloured Petri Nets. J. Intell. Fuzzy Syst. 7(2): 137-149 (1999) - 1998
- [j4]Daniel S. Yeung, Eric C. C. Tsang:
A multilevel weighted fuzzy reasoning algorithm for expert systems. IEEE Trans. Syst. Man Cybern. Part A 28(2): 149-158 (1998) - [c4]Simon C. K. Shiu, Eric C. C. Tsang, Daniel S. Yeung, Martin B. Lam:
Evaluation of printed circuit board assembly manufacturing systems using fuzzy colored Petri nets. SMC 1998: 1506-1511 - [c3]Eric C. C. Tsang, Daniel S. Yeung:
Refining local weights and certainty factors using a fuzzy neural network. SMC 1998: 1512-1517 - [c2]Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee:
Refinement of knowledge representation parameters in fuzzy production rules by genetic algorithms. SMC 1998: 1518-1523 - 1997
- [j3]Daniel S. Yeung, Eric C. C. Tsang:
Weighted fuzzy production rules. Fuzzy Sets Syst. 88(3): 299-313 (1997) - [j2]Daniel S. Yeung, Eric C. C. Tsang:
A comparative study on similarity-based fuzzy reasoning methods. IEEE Trans. Syst. Man Cybern. Part B 27(2): 216-227 (1997) - [c1]Eric C. C. Tsang, Daniel S. Yeung:
Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks. KES (2) 1997: 409-418 - 1994
- [j1]Daniel S. Yeung, Eric C. C. Tsang:
Improved fuzzy knowledge representation and rule evaluation using fuzzy petri nets and degree of subsethood. Int. J. Intell. Syst. 9(12): 1083-1100 (1994)
Coauthor Index
John W. T. Lee
aka: John Wan Tung Lee
aka: John Wan Tung Lee
Xizhao Wang
aka: Xi-Zhao Wang
aka: Xi-Zhao Wang
[j68] [j66] [j53] [j39] [j38] [j37] [j35] [j34] [p1] [j32] [j31] [j30] [j29] [j28] [j27] [j26] [j25] [c29] [c28] [j24] [j23] [j22] [j21] [c27] [c26] [j18] [j17] [j16] [c24] [c22] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [j15] [j14] [j13] [j12] [j11] [j10] [j9] [j8] [j7] [c10] [c9] [j6] [c8] [c7] [c6] [c5] [j5] [j4] [c4] [c3] [c2] [j3] [j2] [c1] [j1]
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