| MGRS: A multi-granulation rough set Y Qian, J Liang, Y Yao, C Dang Information sciences 180 (6), 949-970, 2010 | 872 | 2010 |
| Positive approximation: an accelerator for attribute reduction in rough set theory Y Qian, J Liang, W Pedrycz, C Dang Artificial intelligence 174 (9-10), 597-618, 2010 | 801 | 2010 |
| Incomplete multigranulation rough set Y Qian, J Liang, C Dang IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2009 | 446 | 2009 |
| Multigranulation decision-theoretic rough sets Y Qian, H Zhang, Y Sang, J Liang International journal of approximate reasoning 55 (1), 225-237, 2014 | 413 | 2014 |
| Three-way cognitive concept learning via multi-granularity J Li, C Huang, J Qi, Y Qian, W Liu Information sciences 378, 244-263, 2017 | 390 | 2017 |
| A group incremental approach to feature selection applying rough set technique J Liang, F Wang, C Dang, Y Qian IEEE transactions on knowledge and data engineering 26 (2), 294-308, 2012 | 349 | 2012 |
| Test-cost-sensitive attribute reduction F Min, H He, Y Qian, W Zhu Information Sciences 181 (22), 4928-4942, 2011 | 323 | 2011 |
| Concept learning via granular computing: a cognitive viewpoint J Li, C Mei, W Xu, Y Qian Information Sciences 298, 447-467, 2015 | 302 | 2015 |
| A fitting model for feature selection with fuzzy rough sets C Wang, Y Qi, M Shao, Q Hu, D Chen, Y Qian, Y Lin IEEE Transactions on Fuzzy Systems 25 (4), 741-753, 2016 | 249 | 2016 |
| Feature selection based on neighborhood discrimination index C Wang, Q Hu, X Wang, D Chen, Y Qian, Z Dong IEEE transactions on neural networks and learning systems 29 (7), 2986-2999, 2017 | 245 | 2017 |
| NMGRS: Neighborhood-based multigranulation rough sets G Lin, Y Qian, J Li International Journal of Approximate Reasoning 53 (7), 1080-1093, 2012 | 243 | 2012 |
| Knowledge structure, knowledge granulation and knowledge distance in a knowledge base Y Qian, J Liang, C Dang International Journal of Approximate Reasoning 50 (1), 174-188, 2009 | 240 | 2009 |
| Feature subset selection based on fuzzy neighborhood rough sets C Wang, M Shao, Q He, Y Qian, Y Qi Knowledge-Based Systems 111, 173-179, 2016 | 233 | 2016 |
| Set-valued ordered information systems Y Qian, C Dang, J Liang, D Tang Information Sciences 179 (16), 2809-2832, 2009 | 227 | 2009 |
| Interval ordered information systems Y Qian, J Liang, C Dang Computers & Mathematics with Applications 56 (8), 1994-2009, 2008 | 227 | 2008 |
| An efficient rough feature selection algorithm with a multi-granulation view J Liang, F Wang, C Dang, Y Qian International journal of approximate reasoning 53 (6), 912-926, 2012 | 222 | 2012 |
| An efficient accelerator for attribute reduction from incomplete data in rough set framework Y Qian, J Liang, W Pedrycz, C Dang Pattern Recognition 44 (8), 1658-1670, 2011 | 222 | 2011 |
| Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification L Sun, X Zhang, Y Qian, J Xu, S Zhang Information Sciences 502, 18-41, 2019 | 211 | 2019 |
| Combination entropy and combination granulation in rough set theory Y Qian, J Liang International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2008 | 203 | 2008 |
| Maximal-discernibility-pair-based approach to attribute reduction in fuzzy rough sets J Dai, H Hu, WZ Wu, Y Qian, D Huang IEEE Transactions on Fuzzy Systems 26 (4), 2174-2187, 2017 | 194 | 2017 |
Jiye Liang山西大学计算智能与中文信息处理教育部重点实验室教授Verified email at sxu.edu.cn
