| REDPC: A residual error-based density peak clustering algorithm M Parmar, D Wang, X Zhang, AH Tan, C Miao, J Jiang, Y Zhou Neurocomputing 348, 82-96, 2019 | 80 | 2019 |
| McDPC: Multi-center density peak clustering Y Wang, D Wang, X Zhang, W Pang, C Miao, AH Tan, Y Zhou Neural Computing and Applications 32, 13465-13478, 2020 | 62 | 2020 |
| Methods for labeling error detection in microarrays based on the effect of data perturbation on the regression model C Zhang, C Wu, E Blanzieri, Y Zhou, Y Wang, W Du, Y Liang Bioinformatics 25 (20), 2708-2714, 2009 | 37 | 2009 |
| FREDPC: A feasible residual error-based density peak clustering algorithm with the fragment merging strategy MD Parmar, W Pang, D Hao, J Jiang, W Liupu, L Wang, Y Zhou IEEE Access 7, 89789-89804, 2019 | 36 | 2019 |
| VDPC: Variational density peak clustering algorithm Y Wang, D Wang, Y Zhou, X Zhang, C Quek Information Sciences 621, 627-651, 2023 | 31 | 2023 |
| Deep learning analysis and age prediction from shoeprints M Hassan, Y Wang, D Wang, D Li, Y Liang, Y Zhou, D Xu Forensic Science International 327, 110987, 2021 | 25 | 2021 |
| A computational method for prediction of saliva-secretory proteins and its application to identification of head and neck cancer biomarkers for salivary diagnosis Y Sun, W Du, C Zhou, Y Zhou, Z Cao, Y Tian, Y Wang IEEE Transactions on Nanobioscience 14 (2), 167-174, 2015 | 22 | 2015 |
| A systematic density-based clustering method using anchor points Y Wang, D Wang, W Pang, C Miao, AH Tan, Y Zhou Neurocomputing 400, 352-370, 2020 | 20 | 2020 |
| An interpretable neural fuzzy inference system for predictions of underpricing in initial public offerings D Wang, X Qian, C Quek, AH Tan, C Miao, X Zhang, GS Ng, Y Zhou Neurocomputing 319, 102-117, 2018 | 19 | 2018 |
| Autonomous agents in snake game via deep reinforcement learning Z Wei, D Wang, M Zhang, AH Tan, C Miao, Y Zhou 2018 IEEE International conference on Agents (ICA), 20-25, 2018 | 19 | 2018 |
| An energy-aware spatial index tree for multi-region attribute query aggregation processing in wireless sensor networks J Tang, B Zhang, Y Zhou, L Wang IEEE Access 5, 2080-2095, 2017 | 18 | 2017 |
| Incorporating surprisingly popular algorithm and euclidean distance-based adaptive topology into PSO X Wu, J Han, D Wang, P Gao, Q Cui, L Chen, Y Liang, H Huang, HP Lee, ... Swarm and Evolutionary Computation 76, 101222, 2023 | 17 | 2023 |
| A novel density peak clustering algorithm based on squared residual error M Parmar, D Wang, AH Tan, C Miao, J Jiang, Y Zhou 2017 international conference on security, pattern analysis, and cybernetics …, 2017 | 15 | 2017 |
| LatinPSO: an algorithm for simultaneously inferring structure and parameters of ordinary differential equations models X Tian, W Pang, Y Wang, K Guo, Y Zhou Biosystems 182, 8-16, 2019 | 13 | 2019 |
| ACPNet: A deep learning network to identify anticancer peptides by hybrid sequence information M Sun, S Yang, X Hu, Y Zhou Molecules 27 (5), 1544, 2022 | 12 | 2022 |
| Density propagation based adaptive multi-density clustering algorithm Y Wang, W Pang, Y Zhou Plos one 13 (7), e0198948, 2018 | 12 | 2018 |
| Goods consumed during transit in split delivery vehicle routing problems: Modeling and solution W Yang, D Wang, W Pang, AH Tan, Y Zhou IEEE Access 8, 110336-110350, 2020 | 11 | 2020 |
| Improved gravitation field algorithm and its application in hierarchical clustering M Zheng, Y Sun, G Liu, Y Zhou, C Zhou PloS one 7 (11), e49039, 2012 | 11 | 2012 |
| A general framework for accelerating swarm intelligence algorithms on FPGAs, GPUS and multi-core CPUS D Li, L Huang, K Wang, W Pang, Y Zhou, R Zhang IEEE Access 6, 72327-72344, 2018 | 10 | 2018 |
| Inferring gene regulatory networks by singular value decomposition and gravitation field algorithm M Zheng, J Wu, Y Huang, G Liu, Y Zhou, C Zhou PLoS One 7 (12), e51141, 2012 | 10 | 2012 |
