Monotone fuzzy rule relabeling for the zero-order TSK fuzzy inference system LM Pang, KM Tay, CP Lim IEEE Transactions on Fuzzy systems 24 (6), 1455-1463, 2016 | 21 | 2016 |
Application of self-organizing map to failure modes and effects analysis methodology WL Chang, LM Pang, KM Tay Neurocomputing 249, 314-320, 2017 | 20 | 2017 |
A new framework of evolutionary multi-objective algorithms with an unbounded external archive H Ishibuchi, LM Pang, K Shang TechRxiv, 2020 | 5 | 2020 |
A new framework with similarity reasoning and monotone fuzzy rule relabeling for fuzzy inference systems KM Tay, LM Pang, TL Jee, CP Lim 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2013 | 5 | 2013 |
A new monotonicity index for fuzzy rule-based systems LM Pang, KM Tay, CP Lim 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1566-1570, 2014 | 4 | 2014 |
Multi-expert decision-making with incomplete and noisy fuzzy rules and the monotone test YW Kerk, LM Pang, KM Tay, CP Lim 2016 IEEE international conference on fuzzy systems (FUZZ-IEEE), 94-101, 2016 | 3 | 2016 |
Algorithm configurations of MOEA/D with an unbounded external archive LM Pang, H Ishibuchi, K Shang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 2 | 2020 |
A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems KM Tay, TL Jee, LM Pang, CP Lim 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-7, 2013 | 2 | 2013 |
Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks LM Pang, H Ishibuchi, K Shang IEEE Access 8, 163197-163208, 2020 | 1 | 2020 |
Solution Subset Selection for Final Decision Making in Evolutionary Multi-Objective Optimization H Ishibuchi, LM Pang, K Shang arXiv preprint arXiv:2006.08156, 2020 | 1 | 2020 |
Evolutionary Multi-Objective Optimization Algorithm Framework with Three Solution Sets H Ishibuchi, LM Pang, K Shang arXiv preprint arXiv:2012.07319, 2020 | | 2020 |
NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems LM Pang, H Ishibuchi, K Shang IEEE Access 8, 190240-190250, 2020 | | 2020 |
Population Size Specification for Fair Comparison of Multi-objective Evolutionary Algorithms H Ishibuchi, LM Pang, K Shang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | | 2020 |
Numerical Analysis on Optimal Distributions of Solutions for Hypervolume Maximization H Ishibuchi, LM Pang, K Shang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | | 2020 |
Parallel Implementation of MOEA/D with Parallel Weight Vectors for Feature Selection W Liao, H Ishibuchi, LM Pang, K Shang 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | | 2020 |
A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology LM Pang, KM Tay, CP Lim, H Ishibuchi IEEE Access 8, 144908-144930, 2020 | | 2020 |
A Survey on the Hypervolume Indicator in Evolutionary Multi-objective Optimization K Shang, H Ishibuchi, L He, LM Pang IEEE Transactions on Evolutionary Computation, 2020 | | 2020 |
Robust TSK Fuzzy System based on Semi-Supervised Learning for Label Noise Data T Zhang, Z Deng, H Ishibuchi, LM Pang IEEE Transactions on Fuzzy Systems, 2020 | | 2020 |
Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorithm LM Pang, H Ishibuchi, K Shang 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 1889-1897, 2019 | | 2019 |
Weak Convergence Detection-based Dynamic Reference Point Specification in SMS-EMOA W Liao, K Shang, LM Pang, H Ishibuchi 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 1841-1848, 2019 | | 2019 |