钱宇华 最终学位：博士
导师类型：博士生导师

电子邮箱：jinchengqyh@126.com
联系电话：

研究方向：人工智能、大数据与机器学习等


个人简介
学术论文
科研项目
钱宇华，博士，教授、博士生导师，山西大学大数据科学与产业研究院负责人，计算智能与中文信息处理教育部重点实验室副主任，2018年全球高被引科学家。从事人工智能、大数据、数据挖掘与机器学习等方面的研究。国家优秀青年基金获得者，三晋****，山西省中青年拔尖创新人才，教育部新世纪人才，山西省学术技术带头人，省委联系的高级专家，山西省青年学术带头人。中国人工智能学会粒计算与知识发现专业委员会副主任，中国人工智能学会知识工程与分布智能专委会常务委员，中国计算机学会人工智能与模式识别专业委员会委员，中国人工智能学会机器学习专委会委员，CCF优博轮值主席。
近年来，主持和参与国家重点研发计划、国家自然科学基金优秀青年基金、国家自然科学基金重点项目、教育部新世纪人才计划项目、教育部社科类重点项目等国家级项目20余项。围绕粒计算、机器学习、进化智能、关联学习、复杂网络分析等领域中的共性基础问题开展系统研究，先后在《Artificial Intelligence》、《ACM Transactions on Information Systems》、《ACM Transactions on Knowledge Discovery from Data》、《International Journal of Approximate Reasoning》、《IEEE Transactions on Neural Networks and Learning Systems》、《IEEE Transactions on Knowledge and Data Engineering》、《IEEE Transactions on Fuzzy Systems》、《IEEE Transactions on Systems, Man and Cybernetics》、《Pattern Recognition》、《中国科学》等国际重要期刊发表SCI论文100余篇，获发明专利2 项。
曾获得山西省科学技术奖（自然科学类）一等奖，教育部宝钢教育基金特等奖，CCF 优秀博士论文奖，山西省“五四青年奖章”，全国百篇优秀博士论文提名奖。2014- 2018年，连续入选爱思唯尔中国高被引****榜单。


[1] Feijiang Li, Yuhua Qian, Jieting Wang, Chuangyin Dang, Liping Jing, Clustering ensemble based on sample's stability, Artificial Intelligence, 2019, 273, 37-55.
[2] Anhui Tan, Weizhi Wu, Yuhua Qian, Jiye Liang, Jinkun Chen, Jinjin Li, Intuitionistic fuzzy rough set-based granular structures and attribute subset selection, IEEE Transactions on Fuzzy Systems, 2019, 27(3), 527-539.
[3] Honghong Cheng, Yuhua Qian, Diversity-induced fuzzy clustering, International Journal of Approximate Reasoning, 2019, 106，89-106.
[4] Yan Chen, Qian Guo, Xinyan Liang, Jiang Wang, Yuhua Qian, Environmental sound classification with dilated convolutions, Applied Acoustics, 2019, 148, 123-132.
[5] Xibei Yang, Shaochen Liang, Hualong Yu, Shang Gao, Yuhua Qian, Pseudo-label neighborhood rough set: measures and attribute reductions, International Journal of Approximate Reasoning, 2019, 105, 112-129.
[6] Lin Sun, Xiaoyu Zhang, Yuhua Qian, et al., Joint neighborhood entropy-based gene selection method with fisher score for tumor classification, Applied Intelligence, 2019, In Press.
[7] Feijiang Li, Yuhua Qian, Jieting Wang, Chuangyin Dang, Bing Liu, Cluster's quality evaluation and selective clustering ensemble, ACM Transactions on Knowledge Discovery from Data, 2018, 12(5), 60.
[8] Fuyuan Cao, Joshua Zhexue Huang, Jiye Liang, Xingwang Zhao, Yinfeng Meng, Kai Feng, Yuhua Qian, An algorithm for clustering categorical data with set-valued features, IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(10), 4593-4606.
[9] Jianhua Dai, Hu Hu, Weizhi Wu, Yuhua Qian, Debiao Huang, Maximal discernibility paris based approach to attribute reduction in fuzzy rough sets, IEEE Transactions on Fuzzy Systems, 2018, 26(4), 2174-2187.
[10] Zhongying Zhao, Wenqiang Liu, Yuhua Qian, Liqiang Nie, Yilong Yin, Yong Zhang, Identifying advisor-advisee relationships from co-author networks via a novel deep model, Information Sciences, 2018, 466, 258-269.
[11] Xiaoying Guo, Yuhua Qian, Liang Li, Akira Asano, Assessment model for perceived visual complexity of painting images, Knowledge-Based Systems, 2018, 159, 110-119.
[12] Peng Song, Jiye Liang, Yuhua Qian, Wei Wei, Feng Wang, A cautious ranking methodology with its application for stock screening, Applied Soft Computing, 2018, 71, 835-848.
[13] Qi Wang, Yuhua Qian, Xinyan Liang, Qian Guo, Jiye Liang, Local neighborhood rough set, Knowledge-Based Systems, 2018, 153, 53-64.
[14] Yanhong She, Xiaoli He, Yuhua Qian, Weihua Xu, Jinhai Li, A quantitative approach to reasoning about incomplete knowledge, Information Sciences, 2018, 451-452, 100-111.
[15] Shujiao Liao, Qingxin Zhu, Yuhua Qian, Guoping Lin, Multi-granularity feature selection on cost-sensitive data with measurement errors and variable costs, Knowledge-Based Systems, 2018, 158, 25-42.
[16] Changzhong Wang, Xizhao Wang, Degang Chen, Qinghua Hu, Yuhua Qian. Feature selection based on neighborhood discrimination index, IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(7), 2986 - 2999.
[17] Yuhua Qian, Xinyan Liang, Qi Wang, et al. Local rough set: a solution to rough data analysis in big data, International Journal of Approximate Reasoning, 2018, 97，38-63.
[18] Zhiwei Qiao, Gage Relder, Zhiguo Gui, Yuhua Qian, Boris Epel, Howard Halpern, Three novel accurate pixel-dreven projection methods for 2D CT and 3D EPR imaging, Journal of X-Ray Science and Technology, 2018, 26(1), 83-102
[19] Furong Peng, Xuan Lu, Chao Ma, Yuhua Qian, et al., Multi-level preference regression for cold-start recommendations, International Journal of Machine Learning and Cybernetics, 2017, In Press.
[20] Jie Wang, Wenping Zheng, Yuhua Qian, Jiye Liang, A seed expansion graph clustering method for protein complexes detection in protein interaction networks, Molecules, 2017, 22, 2179, 1-19.
[21] Hang Xu, Wenjian Wang, Yuhua Qian, Fusing complete monotonic decision trees, IEEE Transactions on Knowledge and Data Engineering, 2017, 29(10), 2223 - 2235
[22] Yuhua Qian, Yebin Li, Min Zhang, Guoshuai Ma, Furong Lu, Quantifying edge significance on maintaining global connectivity, Scientific Reports, 2017, DOI: 10.1038/srep45380
[23] Xiaoqiang Guan, Jiye Liang, Yuhua Qian, Jifang Pang, A multi-view OVA model based on decision tree for multi-classification tasks, Knowledge-Based Systems, 2017, 138, 208-219.
[24] Bingzhen Sun, Weimin Ma, Yuhua Qian, Multigranulation fuzzy rough set over two universes and its application to decision making, Knowledge-Based Systems, 2017, 123, 61-74
[25] Yanhong She, Xiaoli He, Huixian Shi, Yuhua Qian, A multiple-valued logic approach for multigranulation rough set model, International Journal of Approximate Reasoning, 2017, 82, 270-284
[26] Yuhua Qian, Xinyan Liang, Guoping Lin, Qian Guo, Jiye Liang, Local multigranulation decision-theoretic rough sets, International Journal of Approximate Reasoning, 2017, 82, 119-137.
[27] Yuhua Qian, Honghong Cheng, Jieting Wang, Jiye Liang, et al., Grouping granular structures in human granulation intelligence, Information Sciences, 2017, 382-382, 150-169.
[28] Feijiang Li, Yuhua Qian, Jieting Wang, Jiye Liang. Multigranulation information fusion: a Dempster-Shafer evidence theory-based clustering ensemble method. Information Sciences, 2017, 378, 309-409
[29] Jinhai Li, Chenchen Huang, Jianjun Qi, Yuhua Qian, Wenqi Liu, Three-way concept learning via multi-granularity, Information Sciences, 2017, 378, 244-263.
[30] Weizhi Wu, Yuhua Qian, Tongjun Li, Shenming Gu, On rule acquisition in incomplete multi-scale decision tables, Information Sciences, 2017, 378, 282-302.
[31] Yuhua Qian, Feijiang Li, Jiye Liang, Bing Liu, Chuangyin Dang. Space structure and clustering of categorical data. IEEE Transactions on Neural Networks and Learning Systems 2016, 27(10): 2047-2059.
[32] Zhiqiang Wang, Jiye Liang, Ru Li, Yuhua Qian, An approach to cold-start link prediction: establishing connections between non-topological and topological information, IEEE Transactions on Knowledge and Data Engineering, 2016, 28(11), 2857-2870.
[33] Changzhong Wang, Mingwen Shao, Qiang He, Yuhua Qian, Yali Qi, Feature subset selection based on fuzzy neighborhood rough sets, Knowledge-Based Systems, 2016, 111(1): 173-179.
[34] Changzhong Wang, Yali Qi, Mingwen Shao, Qinghua Hu, Degang Chen, Yuhua Qian, Yaojin Lin. A fitting model for feature selection with fuzzy rough sets, IEEE Transactions on Fuzzy Systems, 2016 (In Press)
[35] Yinfeng Meng, Jiye Liang, Yuhua Qian, Comparison study of orthonormal representations of functional data in classification, Knowledge-Based Systems, 2016, 97, 224-236.
[36] Guoping Lin, Jiye Liang, Yuhua Qian, Jinjin Li. A fuzzy multigranulation decision-theoretic approach to multi-source fuzzy information systems, Knowledge-Based Systems, 2016, 91: 102-113
[37] Yanli Sang, Jiye Liang, Yuhua Qian, Decision-theoretic rough sets under dynamic granulation, Knowledge-Based Systems, 2016, 91: 84-92.
[38] Jinhai Li, Yue Ren, Changlin Mei, Yuhua Qian, Xibei Yang, A comparative study of multigranulation rough sets and concept lattices via rule acquisition, Knowledge-Based Systems, 2016, 91, 152-164.
[39] Yuhua Qian, Hang Xu, Jiye Liang, Bing Liu, Jieting Wang, Fusing monotonic decision trees, IEEE Transactions on Knowledge and Data Engineering, 2015, 27(10), 2717-2728.
[40] Yuhua Qian, Yebin Li, Jiye Liang, Guoping Lin, Chuangyin Dang, Fuzzy granular structure distance, IEEE Transactions on Fuzzy Systems 2015, 23(6), 2245-2259.
[41] Jiye Liang, Yuhua Qian, Deyu Li, Qinghua Hu, Theory and method of granular computing for big data discovery, Science in China-Series E: Information Sciences (中国科学）, 2015, 45(11):1355-1369.
[42] Zhiwei Qiao, Gage Redler, Boris Epel, Yuhua Qian, Howard Halpern. 3D pulse EPR imaging from sparse-view projections via constrained, total variation minimization. Journal of Magnetic Resonance, 2015, 258， 49-57.
[43] Zhiwei Qiao, Gage Redler, Boris Epel, Yuhua Qian, Howard Halpern. Implementation of GPU-Accelerated Back Projection for EPR imaging. Journal of X Ray Science and Technology, 2015, In Press
[44] Guoping Lin, Jiye Liang, Yuhua Qian, An information fusion approach by combining multigranulation rough sets and evidence theory, Information Sciences, 2015, 314, 184-199.
[45] Baoli Wang, Jiye Liang, Yuhua Qian, Chuangyin Dang, A normalized numerical scaling method for the unbalanced multi-granular linguistic sets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2015, 23(2), 221-243.
[46] Jinhai Li, Changlin Mei, Weihua Xu, Yuhua Qian, Concept learning via granular computing-a cognitive viewpoint, Information Sciences, 2015, 298, 447-467.
[47] Guoping Lin, Jiye Liang, Yuhua Qian, Uncertainty measures for multigranulation approximation space, International Journal of Uncertianty, Fuzziness and Knowledge-Based Systems, 2015, 23(3), 443-457.
[48] Yuhua Qian, Qi Wang, Honghong Cheng, Jiye Liang, Chuangyin Dang. Fuzzy-rough feature selection accelerator, Fuzzy Sets and Systems, 2015, 258, 61-78.
[49] Yuhua Qian, Hu Zhang, Feijiang Li, Qinghua Hu, Jiye Liang. Set-Based Granular Computing: a Lattice Model. International Journal of Approximate Reasoning, 2014, 55, 834-852.
[50] Yali Lv, Shizhong Liao, Hongbo Shi, Yuhua Qian, Suqin Ji. QMIQPN: An enhanced QPN based on qualitative mutual information for reducing ambiguity, Knowledge-Based Systems, 2014, 71, 114-125.
[51] Baoli Wang, Jiye Liang, Yuhua Qian. Preorder information based atribute weights learning in mulitattribute decision making. Fundamenta Informaticae, 2014, 132, 331-347.
[52] Jiye Liang, Feng Wang, Chuangyin Dang, Yuhua Qian. Incremental approach to feature selection based on rough set theory. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(2) 294-308.
[53] Baoli Wang, Jiye Liang, Yuhua Qian. Determining decision maker's weights in group ranking: a granular computing method. International Journal of Machine Learning and Cybernetics, 2014, (In Press).
[54] Yuhua Qian, Shunyong Li, Jiye Liang, Zhongzhi Shi, Feng Wang. Pessimistic rough set based decisions: a multigranulation fusion strategy, Information Sciences, 2014, 264, 196-210.
[55] Xin Liu, Yuhua Qian, Jiye Liang. A rule-extraction framework under multigranulation rough sets. International Journal of Machine Learning and Cybernetics, 2014, 5: 319-326.
[56] Guoping Lin, Jiye Liang, Yuhua Qian, Topological approach to multigranulation rough sets. International Journal of Machine Learning and Cybernetics, 2014, 5: 233-243.
[57] Yuhua Qian, Hu Zhang, Yanli Sang, Jiye Liang. Multigranulation decision-theoretic rough sets, International Journal of Approximate Reasoning, 2014, 55, 225-237.
[58] Guoping Lin, Jiye Liang, Yuhua Qian. Multigranulation rough sets: from partition to covering, Information Sciences, 241 (2013) 101-118.
[59] Xibei Yang, Yuhua Qian, Jingyu Yang, On characterizing hierarchies of granulation structures, Fundamenta Informaticae, 123 (2013) 365-380.
[60] Wei Wei, Jiye Liang, Junhong Wang, Yuhua Qian. Decision-relative discernibility matrixes in the sense of entropies. International Journal of General Systems, 2013, 42(7): 721-738.
[61] Feng Wang, Jiye Liang, Yuhua Qian. Attribute reduction: A dimension incremental strategy, Knowledge-Based Systems, 2013,39:95-108.
[62] Wei Wei, Jiye Liang, Yuhua Qian, Chuangyin Dang, Can fuzzy entropies be effective measure for evaluating the roughness of a rough set? Information Sciences, 2013, 232: 143-166.
[63] Xibei Yang, Yuhua Qian, Jingyu Yang. Hierarchical structures on multigranulation spaces. Journal of Computer Science and Technology, 2012, 27(6): 1169-1183.
[64] Guoping Lin, Yuhua Qian, Jinjin Li. NMGRS: Neighborhood-based multigranulation rough sets. International Journal of Approximate Reasoning, 2012, 53: 1080-1093.
[65] Yuhua Qian, Jiye Liang, Peng Song, Chuangyin Dang, Wei Wei. Evaluation of the decision performance of the decision rule set from an ordered decision table. Knowledge-Based Systems, 2012, 36: 39–50.
[66] Jiye Liang, Feng Wang, Chuangyin Dang, Yuhua Qian. An efficient rough feature selection algorithm with a multi-granulation view. International Journal of Approximate Reasoning, 2012, 53, 912-926.
[67] Yuhua Qian, Jiye Liang, Weiwei. Consistency-preserving attribute reduction in fuzzy rough set framework. International Journal of Maching Learning and Cybernetics, 2012, 45-53.
[68] Yuhua Qian, Jiye Liang, Weizhi Wu, Chuangyin Dang. Partial orderings of information granulations-a further investigation. Expert Systems, 2012, 29(1), 3-24.
[69] Jiye Liang, Ru Li, Yuhua Qian. Distance-a more comprehensive perspective for measures in rough set theory. Knowledge-Based Systems, 2012, 27, 126-136.
[70] Wei Wei, Jiye Liang, Yuhua Qian. A comparative study of rough sets for hybrid data. Information Sciences, 2012, 190(1), 1-16.
[71] Peng Song, Jiye Liang, Yuhua Qian. A two-grade approach to ranking interval data. Knowledge-Based Systems, 2012, 27, 234-244.
[72] Yuhua Qian, Jiye Liang, Weizhi Wu, Chuangyin Dang. Information granularity in fuzzy binary GrC model. IEEE Transactions on Fuzzy Systems, 2011, 19(2), 253-264.
[73] Yuhua Qian, Jiye Liang, Witold Pedrycz, Chuangyin Dang. An efficient accelerator for attribute reduction from incomplete data in rough set framework. Pattern Recognition, 2011, 44, 1658-1670.
[74] Yuhua Qian, Jiye Liang, Feng Wang. 面向非完备决策表的正向近似特征选择加速算法. 计算机学报，2011, 34(3), 435-442.
[75] Fan Min, Huaping He, Yuhua Qian, William Zhu, Test-cost-sensitive attribute reduction, Information Sciences, 2011, 181, 4928-4942.
[76] Yuhua Qian, Jiye Liang, Peng Song, Chuangyin Dang. On dominance relations in disjunctive set-valued ordered information systems. International Journal of Information Technology & Decision Making, 2010, 9(1), 9-33.
[77] Yuhua Qian, Jiye Liang, Yiyu Yao, Chuangyin Dang. MGRS: a multigranulation rough set. Information Sciences, 2010, 180, 949-970.
[78] Yuhua Qian, Jiye Liang, Witold Pedrycz, Chuangyin Dang. Positive approximation: an accelerator for attribute reduction in rough set theory. Artificial Intelligence, 2010, 174, 597-618.
[79] Wei Wei, Jiye Liang, Yuhua Qian, Feng Wang, Chuangyin Dang. Comparative study of decision performance of decision tables induced by attribute reductions, International Journal of General Systems, 2010, 39(8), 813-838.
[80] Yuhua Qian, Jiye Liang, Chuangyin Dang. Incomplete multigranulation rough set. IEEE Transactions on Systems, Man and Cybernetics-Part A, 2010, 40(2), 420-431.
[81] Yuhua Qian, Jiye Liang, Deyu Li, Feng Wang, Nannan Ma. Approximation reduction in inconsistent incomplete decision tables. Knowledge-Based Systems, 2010, 23(5), 427-433.
[82] Yuhua Qian, Jiye Liang, Chuangyin Dang. Knowledge structure, knowledge granulation and knowledge distance in a knowledge base. International Journal of Approximate Reasoning, 2009, 50(1), 174-188.
[83] Yuhua Qian, Jiye Liang, Chuangyin Dang, Dawei Tang. Set-valued ordered information systems, Information Sciences, 2009, 179, 2809-2832.
[84] Yuhua Qian, Jiye Liang, Feng Wang. A new method for measuring the uncertainty in incomplete information systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2009, 17(6), 855-880.
[85] Jiye Liang, Junhong Wang, Yuhua Qian. A new measure of uncertainty based on based on knowledge granulation for rough sets. Information Sciences, 2009, 179, 458-470.
[86] 梁吉业，钱宇华. 信息系统中的信息粒与熵理论. 中国科学E辑：信息科学， 2008, 38(12), 2048-2065.
[87] Yuhua Qian, Jiye Liang, Chuangyin Dang, Haiyun Zhang, Jianmin Ma. On the evaluation of the decision performance of an incomplete decision table. Data & Knowledge Engineering, 2008, 65(3), 373-400.
[88] Yuhua Qian, Jiye Liang, Chuangyin Dang. Consistency measure, inclusion degree and fuzzy measure in decision tables. Fuzzy Sets and Systems, 2008, 159, 2353-2377.
[89] Jiye Liang, Yuhua Qian. Information granules and entropy theory in information systems. Science in China, Series F: Information Sciences, 2008, 51(10), 1427-1444.
[90] Yuhua Qian, Jiye Liang, Chuangyin Dang. Interval ordered information systems, Computers & Mathematics with Applications, 2008, 56, 1994-2009.
[91] Yuhua Qian, Jiye Liang. Combination entropy & combination granulation in rough set theory. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2008, 16(2), 179-193.
[92] Yuhua Qian, Jiye Liang, Chuangyin Dang. Converse approximation and rule extraction from decision tables in rough set theory, Computers & Mathematics with Applications, 2008, 55, 1754-1765.
[93] Junhong Wang, Jiye Liang, Yuhua Qian, Chuangyin Dang. uncertainty measure of rough sets based on a knowledge granulation for incomplete information systems, 2008, 16(2), 233-244.
[94] Yuhua Qian, Jiye Liang, Deyu Li, Haiyun Zhang, Chuangyin Dang. Measures for evaluating the decision performance of a decision table in rough set theory. Information Sciences, 2008, 178(1), 181-202.




1. 国家重点研发计划子课题(2018YFB**): 自动深层化知识处理方法与技术，2018/05-2021/04，(主持人)
2. 国家自然科学优秀青年基金(**):智能信息处理，2014/01-2016/12，(主持人)
3. 三晋****（****）:计算机科学与技术，2017/01-2021/12，(主持人)
4. 国家自然科学基金面上项目(**):面向多模态数据的多粒度计算理论与方法，2017/01-2020/12，(主持人)
5. 山西省教育厅高等学校中青年拔尖创新人才支持计划(02**1):大数据关联关系挖掘的理论与方法，2017/01-2019/12，(主持人)
6. 教育部新世纪人才支持计划，2**，基于认知机理的多模态海量数据知识发现，2013/01-2015/12，(主持人)