Journal Papers

2022 (15 篇)
[15] Tian Yang, Yanfang Deng, Bin Yu, Yuhua Qian, Jianhua Dai, Local Feature Selection for Large-scale Data Sets with Limited Labels,IEEE Transactions on Knowledge and Data Engineering,2022,In Press
[14] Jieting Wang,Yuhua Qian,Feijiang Li,Jiye Liang,Qingfu Zhang,Generalization Performance of Pure Accuracy and Its Application in Selective Ensemble Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 In Press
[13] Honghong Cheng, Yuhua Qian,Yingjie Guo, Keyin Zheng, Qingfu Zhang,Neighborhood Information-based Method for Multivariate Association Mining,IEEE Transactions on Knowledge and Data Engineering,2022,In Press
[12] Tao Yan, Yuhua Qian, Feijiang Li, Hongren Yan, Jieting Wang, Jiye Liang, Keyin Zheng, Peng Wu, Lu Chen, Zhiguo Hu, Zhiwei Qiao, Jiangfeng Zhang, Xiaopeng Zhai, Intelligent microscopic 3D shape reconstruction method based on 3D time-frequency transformation, 中国科学:信息科学, 2022, In Press.
[11] Xinyan Liang, Yuhua Qian, Qian Guo, Honghong Cheng, Jiye Liang, AF: an association-based fusion method for multi-modal classification, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022,doi: 10.1109/TPAMI.2021.3125995.
[10] Qian Guo, Yuhua Qian, Xinyan Liang. GLRM: Logical pattern mining in the case of inconsistent data distribution based on multigranulation strategy[J]. International Journal of Approximate Reasoning, 2022,4(143):78-101.
[9] Chao Wen, Yu Xie, Zhiwei Qiao, Liyun Xu, and Yuhua Qian, A tensor generalized weighted linear predictor for FDA-MIMO radar parameter estimation, IEEE Transactions on Vehicular Technology,2022,In Press
[8] Shilin Gu,Yuhua Qian,Chenping Hou, Incremental feature spaces learning with label scarcity, ACM Transactions on Knowledge Discovery from Data,2022,In Press.
[7] Chao Zhang,Huaxiong Li,Yuhua Qian,Chunlin Chen,Xianzhong Zhou, Locality-constrained discriminative matrix regression for robust face identification, IEEE Transactions on Neural Networks and Learning Systems,2022,33(3):1254-1268.
[6] Yu xie,Shengze Lv, Yuhua Qian,Chao Wen,JiyeLiang, Active and semi-supervised graph neural networks for graph classification, IEEE Transactions on Big Data, 2022,doi: 10.1109/TBDATA.2021.3140205.
[5] Keqi Wang, Yuhua Qian, Jiye Liang, Chang Liu, Qin Huang, Lu Chen, Jieru jia, Local-global coupling relationship based low-light image enhancement, 中国科学:信息科学, 2022, In Press.
[4] Changzhong Wang, Yuhua Qian, Weiping Ding, Xiaodong Feng, Feature selection with fuzzy-rough minimum classification error criterion, IEEE Transactions on Fuzzy Systems, 2021, doi: 10.1109/TFUZZ.2021.3097811.
[3] Zhehuang Huang, Jinjin Li, Yuhua Qian, Noise-tolerant fuzzy covering based multigranulation rough sets and feature subset selection, IEEE Transactions on Fuzzy Systems, 2021, doi: 10.1109/TFUZZ.2021.3093202.
[2] Lin Sun, Tengyu Yin, Weiping Ding, Yuhua Qian, Jiucheng Xu, Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy, IEEE Transactions on Fuzzy Systems, 2021, doi: 10.1109/TFUZZ.2021.3053844.
[1] Chao Zhang, Huaxiong Li, Chunlin Chen, Yuhua Qian, Xianzhong Zhou, Enhanced group sparse regularized nonconvex regression for face recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, doi: 10.1109/TPAMI.2020. 3033994.
2021 (11 篇)
[11] Xinyan Liang, Qian Guo, Yuhua Qian, Weiping Ding, Qingfu Zhang, Evolutionary deep fusion method and its application in chemical structure recognition, IEEE Transactions on Evolutionary Computation, 2021, 25(5):883-893.
[10] Gaoxia Jiang, Wenjian Wang, Yuhua Qian, Jiye Liang, A unified sample selection framework for output noise filtering: an error-bound perspective, Journal of Machine Learning Research, 2021, 22, 1-66.
[9] Qian Guo, Yuhua Qian, Xinyan Liang, Yanhong She, Deyu Li, Jiye Liang, Logic could be learned from images, International Journal of Machine Learning and Cybernetics, 2021, 12, 3397-3414.
[8] Guoshuai Ma, Hongren Yan, Yuhua Qian, Lingfeng Wang, Chuangyin Dang, Zhongying Zhao, Path-based estimation for link prediction, International Journal of Machine Learning and Cybernetics, 2021, 12, 2443-2458.
[7] Jue Li, Feng Cao, Honghong Cheng, Yuhua Qian, Learning the number of filters in convolutional neural networks, International Journal of Bio-Inspired Computation, 2021, 17(2):75-84.
[6] Jing Pan, Yuhua Qian, Feijiang Li, Qian Guo, Image deep clustering based on local-topology embedding, Pattern Recognition Letters, 2021, 151, 88-94.
[5] Yali Lv, Junzhong Miao, Jiye Liang, Ling Chen, Yuhua Qian, BIC-based node order learning for improving Bayesian network structure learning, Frontiers of Computer Science, 2021, 15(6): 156337.
[4] Tianxing Wang, Huaxiong Li, Yuhua Qian, Bing Huang, Xianzhong Zhou, A regret-based three-way decision model under interval Type-2 fuzzy environment, IEEE Transactions on Fuzzy Systems, 2020, doi: 10.1109/TFUZZ.2020.3033448.
[3] Zehua Jiang, Keyu Liu, Jingjing Song, Xibei Yang, Jinhai Li, Yuhua Qian, Accelerator for crosswise computing reduct, Applied Soft Computing Journal, 2021, 98: 106740.
[2] Chao Zhang, Huaxiong Li, Yuhua Qian, Chunlin Chen, Yang Gao, Pairwise relations oriented discriminative regression, IEEE Transactions on Circuits and Systems for Video Technology, 2021, 31(7):2646-2660.
[1] Lin Sun, Lanying Wang, Weiping Ding, Yuhua Qian, Jiucheng Xu, Feature selection using fuzzy neighborhood entropy-based uncertainty measures for fuzzy neighborhood multigranulation rough sets, IEEE Transactions on Fuzzy Systems, 2021, 29(1):19-33.
2020 (10 篇)
[10] Jieting Wang, Yuhua Qian, Feijiang Li, Learning with mitigating random consistency from the accuracy measure, Machine Learning, 2020, 109, 2247–2281.
[9] Hong Tao, Chenping Hou, Yuhua Qian, Jubo Zhu, Dongyun Yi, Latent complete row sapce recovery for multi-view subspace clustering, IEEE Transactions on Image Processing, 2020, 29, 8083-8096.
[8] Honghong Cheng, Yuhua Qian, Zhiguo Hu, Jiye Liang, Association mining method based on neighborhood. 中国科学:信息科学, 2020, 50(6), 824-844.
[7] Peng Zhou, Liang Du, Xuejun Li, Yidong Shen, Yuhua Qian, Unsupervised feature selection with adaptive multiple graph learning, Pattern Recognition, 2020, 105, 107375.
[6] Tian Yang, Xiaru Zhong, Guangming Lang, Yuhua Qian, Jianhua Dai, Granular matrix: a new approach for granular structure reduction and redundancy evaluation, IEEE Transactions on Fuzzy Systems, 2020, 28(12), 3133-3144.
[5] Kun Sun, Wenbing Tao, Yuhua Qian, Guide to match: multi-layer feature matching with a hybrid gaussian mixture model. IEEE Transactions on Multimedia, 2020, 22(9), 2246-2261.
[4] Feijiang Li, Yuhua Qian, jieting Wang, Jiye Liang, Wenjian Wang, Clustering method based on sample's stability, 中国科学: 信息科学, 2020, 50(8), 1239-1254.
[3] Jieting Wang, Yuhua Qian, Feijiang Li, Jiye Liang, Weiping Ding, Fusing fuzzy monotonic decision trees, IEEE Transactions on Fuzzy Systems, 2020, 28(5), 887-900.
[2] Changzhong Wang, Yan Wang, Mingwen Shao, Yuhua Qian, Degang Chen, Fuzzy rough attribute reduction for categorical data, IEEE Transactions on Fuzzy Systems, 2020, 28(5), 818-830.
[1] Tao Yan, Zhiguo Hu, Yuhua Qian, Zhiwei Qiao, Linyuan Zhang, 3D shape reconstruction from multifocus image fusion using a multidirectional modified Laplacian operator, Pattern Recognition, 2020, 98, 107065.
2019 (14 篇)
[14] Huafeng Liu, Liping Jing, Yuhua Qian, Jian Yu, Adaptive local low-rank matrix approximation for recommendation, ACM Transactions on Information Systems, 2019, 37(4), 45.
[13] Feijiang Li, Yuhua Qian, Jieting Wang, Chuangyin Dang, Liping Jing, Clustering ensemble based on sample's stability, Artificial Intelligence, 2019, 273, 37-55.
[12] 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.
[11] Jianmin Ma, Lingling Hu, Yuhua Qian, Object-oriented interval-set concept lattices, International Journal of Approximate Reasoning, 2019, 110, 64-81.
[10] Lin Sun, Lanying Wang, Yuhua Qian, Jiucheng Xu, Shiguang Zhang, Feature selection using Lebesgue and entropy measures for incomplete neighborhood decision systems, Knowledge-Based Systems, 2019, 186(15), 104942.
[9] Lin Sun, Xiaoyu Zhang, Yuhua Qian, Jiucheng Xu, Shiguang Zhang, Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification, Information Sciences, 2019, 502, 18-41.
[8] Keyu Liu, Xibei Yang, Hamido Fujita, Dun Liu, Xin Yang, Yuhua Qian, An efficient selector for multi-granularity attribute reduction, Information Sciences, 2019, 505, 457-472.
[7] Zehua Jiang, Xibei Yang, Hualong Yu, Dun Liu, Pingxin Wang, Yuhua Qian, Accelerator for multi-granularity attribute reduction, Knowledge-Based Systems, 2019, 177, 145-158.
[6] Shujiao Liao, Qingxin Zhu, Yuhua Qian, Feature–granularity selection with variable costs for hybrid data, Soft Computing, 2019, doi.org/10.1007/s00500-019-03854-2
[5] Zhangjian Ji, Kai Feng, Yuhua Qian, Part-based visual tracking via structural support correlation filter, Journal of Visual Communication and Image Representation, 2019, 102602.
[4] Honghong Cheng, Yuhua Qian, Diversity-induced fuzzy clustering, International Journal of Approximate Reasoning, 2019, 106,89-106.
[3] Yan Chen, Qian Guo, Xinyan Liang, Jiang Wang, Yuhua Qian, Environmental sound classification with dilated convolutions, Applied Acoustics, 2019, 148, 123-132.
[2] 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.
[1] 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.
2018 (13 篇)
[13] 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.
[12] 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.
[11] Jianhua Dai, Hu Hu, Weizhi Wu, Yuhua Qian, Debiao Huang, Maximal discernibility pairs 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.
[9] Xiaoying Guo, Yuhua Qian, Liang Li, Akira Asano, Assessment model for perceived visual complexity of painting images, Knowledge-Based Systems, 2018, 159, 110-119.
[8] 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.
[7] Qi Wang, Yuhua Qian, Xinyan Liang, Qian Guo, Jiye Liang, Local neighborhood rough set, Knowledge-Based Systems, 2018, 153, 53-64.
[6] 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.
[5] 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.
[4] 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.
[3] 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.
[2] 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
[1] 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, 2018, 9:1117-1130.
2017 (11 篇)
[11] 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.
[10] Hang Xu, Wenjian Wang, Yuhua Qian, Fusing complete monotonic decision trees, IEEE Transactions on Knowledge and Data Engineering, 2017, 29(10), 2223 - 2235
[9] Yuhua Qian, Yebin Li, Min Zhang, Guoshuai Ma, Furong Lu, Quantifying edge significance on maintaining global connectivity, Scientific Reports, 2017, DOI: 10.1038/srep45380
[8] 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.
[7] 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
[6] 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
[5] 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.
[4] Yuhua Qian, Honghong Cheng, Jieting Wang, Jiye Liang, et al., Grouping granular structures in human granulation intelligence, Information Sciences, 2017, 382-382, 150-169.
[3] 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
[2] Jinhai Li, Chenchen Huang, Jianjun Qi, Yuhua Qian, Wenqi Liu, Three-way concept learning via multi-granularity, Information Sciences, 2017, 378, 244-263.
[1] Weizhi Wu, Yuhua Qian, Tongjun Li, Shenming Gu, On rule acquisition in incomplete multi-scale decision tables, Information Sciences, 2017, 378, 282-302.
2016 (8 篇)
[8] 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.
[7] 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.
[6] 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.
[5] 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)
[4] Yinfeng Meng, Jiye Liang, Yuhua Qian, Comparison study of orthonormal representations of functional data in classification, Knowledge-Based Systems, 2016, 97, 224-236.
[3] 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
[2] Yanli Sang, Jiye Liang, Yuhua Qian, Decision-theoretic rough sets under dynamic granulation, Knowledge-Based Systems, 2016, 91: 84-92.
[1] 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.
2015 (10 篇)
[10] 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.
[9] Yuhua Qian, Yebin Li, Jiye Liang, Guoping Lin, Chuangyin Dang, Fuzzy granular structure distance, IEEE Transactions on Fuzzy Systems 2015, 23(6), 2245-2259.
[8] 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.
[7] 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.
[6] 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
[5] Guoping Lin, Jiye Liang, Yuhua Qian, An information fusion approach by combining multigranulation rough sets and evidence theory, Information Sciences, 2015, 314, 184-199.
[4] 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.
[3] Jinhai Li, Changlin Mei, Weihua Xu, Yuhua Qian, Concept learning via granular computing-a cognitive viewpoint, Information Sciences, 2015, 298, 447-467.
[2] 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.
[1] Yuhua Qian, Qi Wang, Honghong Cheng, Jiye Liang, Chuangyin Dang. Fuzzy-rough feature selection accelerator, Fuzzy Sets and Systems, 2015, 258, 61-78.
2014 (9 篇)
[9] 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.
[8] 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.
[7] Baoli Wang, Jiye Liang, Yuhua Qian. Preorder information based atribute weights learning in mulitattribute decision making. Fundamenta Informaticae, 2014, 132, 331-347.
[6] 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.
[5] 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).
[4] 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.
[3] 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.
[2] Guoping Lin, Jiye Liang, Yuhua Qian, Topological approach to multigranulation rough sets. International Journal of Machine Learning and Cybernetics, 2014, 5: 233-243.
[1] Yuhua Qian, Hu Zhang, Yanli Sang, Jiye Liang. Multigranulation decision-theoretic rough sets, International Journal of Approximate Reasoning, 2014, 55, 225-237.
2013 (5 篇)
[5] Guoping Lin, Jiye Liang, Yuhua Qian. Multigranulation rough sets: from partition to covering, Information Sciences, 241 (2013) 101-118.
[4] Xibei Yang, Yuhua Qian, Jingyu Yang, On characterizing hierarchies of granulation structures, Fundamenta Informaticae, 123 (2013) 365-380.
[3] 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.
[2] Feng Wang, Jiye Liang, Yuhua Qian. Attribute reduction: A dimension incremental strategy, Knowledge-Based Systems, 2013,39:95-108.
[1] 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.
2012 (9 篇)
[9] Xibei Yang, Yuhua Qian, Jingyu Yang. Hierarchical structures on multigranulation spaces. Journal of Computer Science and Technology, 2012, 27(6): 1169-1183.
[8] Guoping Lin, Yuhua Qian, Jinjin Li. NMGRS: Neighborhood-based multigranulation rough sets. International Journal of Approximate Reasoning, 2012, 53: 1080-1093.
[7] 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.
[6] 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.
[5] Yuhua Qian, Jiye Liang, Weiwei. Consistency-preserving attribute reduction in fuzzy rough set framework. International Journal of Maching Learning and Cybernetics, 2012, 45-53.
[4] Yuhua Qian, Jiye Liang, Weizhi Wu, Chuangyin Dang. Partial orderings of information granulations-a further investigation. Expert Systems, 2012, 29(1), 3-24.
[3] Jiye Liang, Ru Li, Yuhua Qian. Distance-a more comprehensive perspective for measures in rough set theory. Knowledge-Based Systems, 2012, 27, 126-136.
[2] Wei Wei, Jiye Liang, Yuhua Qian. A comparative study of rough sets for hybrid data. Information Sciences, 2012, 190(1), 1-16.
[1] Peng Song, Jiye Liang, Yuhua Qian. A two-grade approach to ranking interval data. Knowledge-Based Systems, 2012, 27, 234-244.
2011 (4 篇)
[4] 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.
[3] 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.
[2] 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.
[1] Fan Min, Huaping He, Yuhua Qian, William Zhu, Test-cost-sensitive attribute reduction, Information Sciences, 2011, 181, 4928-4942.
2010 (6 篇)
[6] 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.
[5] Yuhua Qian, Jiye Liang, Yiyu Yao, Chuangyin Dang. MGRS: a multigranulation rough set. Information Sciences, 2010, 180, 949-970.
[4] 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.
[3] 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.
[2] Yuhua Qian, Jiye Liang, Chuangyin Dang. Incomplete multigranulation rough set. IEEE Transactions on Systems, Man and Cybernetics-Part A, 2010, 40(2), 420-431.
[1] 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.
2009 (4 篇)
[4] 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.
[3] Yuhua Qian, Jiye Liang, Chuangyin Dang, Dawei Tang. Set-valued ordered information systems, Information Sciences, 2009, 179, 2809-2832.
[2] 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.
[1] 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.
2008 (9 篇)
[9] 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.
[8] 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.
[7] Yuhua Qian, Jiye Liang, Chuangyin Dang. Consistency measure, inclusion degree and fuzzy measure in decision tables. Fuzzy Sets and Systems, 2008, 159, 2353-2377.
[6] Jiye Liang, Yuhua Qian. Information granules and entropy theory in information systems. Science in China, Series F: Information Sciences, 2008, 51(10), 1427-1444.
[5] Yuhua Qian, Jiye Liang, Chuangyin Dang. Interval ordered information systems, Computers & Mathematics with Applications, 2008, 56, 1994-2009.
[4] 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.
[3] 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.
[2] 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.
[1] 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.