q阶犹豫模糊集及其在决策中的应用

doi:10.16451/j.cnki.issn1003-6059.201809005

Abstract
Figure/Table
References (0)
Related Citation (15)

[1] BLUM A L, LANGLEY P. Selection of Relevant Features and Examples in Machine Learning. Artificial Intelligence, 1997, 97(1/2): 245-271.
[2] LIU H, MOTODA H. Feature Extraction, Construction and Selection: A Data Mining Perspective. Boston, USA: Kluwer Academic Publishers, 2001.
[3] PAWLAK Z. Rough Sets: Theoretical Aspects of Reasoning about Data. Boston, USA: Kluwer Academic Publishers, 1991.
[4] PAWLAK Z. Rough Sets. International Journal of Computer and Information Sciences, 1982, 11: 341-356.
[5] 周献中,黄兵,李华雄,等.不完备信息系统知识获取的粗糙集理论与方法.南京:南京大学出版社, 2010. (ZHOU X Z, HUANG B, LI H X，et al. Rough Sets Theory and Approaches for Knowledge Acquisition in Incomplete Information Systems. Nanjing, China: Nanjing University Press, 2010.)
[6] 张文修,吴伟志,梁吉业,等.粗糙集理论与方法.北京:科学出版社, 2001. (ZHANG W X, WU W Z, LIANG J Y，et al. Rough Set Theory and Methods. Beijing, China: Science Press, 2001.)
[7] 梁吉业,李德玉.信息系统中的不确定性与知识获取.北京:科学出版社, 2005. (LIANG J Y, LI D Y. The Uncertainty and Knowledge Acquisition in Information Systems. Beijing, China: Science Press, 2005.)
[8] 苗夺谦,李德毅,姚一豫,等.不确定性与粒计算.北京:科学出版社, 2011. (MIAO D Q, LI D Y, YAO Y Y，et al. Uncertainty and Granular Computing. Beijing, China: Science Press, 2011.)
[9] 王国胤,于洪,杨大春.基于条件信息熵的决策表约简.计算机学报, 2002, 25(7): 759-766. (WANG G Y, YU H, YANG D C. Decision Table Reduction Based on Conditional Information Entropy. Chinese Journal of Computers, 2002, 25(7): 759-766.)
[10] 苗夺谦,胡桂荣.知识约简的一种启发式算法.计算机研究与发展, 1999, 36(6): 681-684. (MIAO D Q, HU G R. A Heuristic Algorithm for Reduction of Knowledge. Journal of Computer Research and Development, 1999, 36(6): 681-684.)
[11] MI J S, WU W Z, ZHANG W X. Approaches to Knowledge Reduction Based on Variable Precision Rough Set Model. Information Sciences, 2004, 159(3/4): 255-272.
[12] HU Q H, YU D R, XIE Z X. Information Preserving Hybrid Data Reduction Based on Fuzzy Rough Techniques. Pattern Recognition Letters, 2006, 27(5): 414-423.
[13] WU W Z. Attribute Reduction Based on Evidence Theory in Incomplete Decision Systems. Information Sciences, 2008, 178(5): 1355-1371.
[14] 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), 2008, 38(12): 2048-2065. (LIANG J Y, QIAN Y H. Information Granules and Entropy Theory in Information Systems. Science in China(Series E), 2008, 38(12): 2048-2065.)
[15] 刘少辉,盛秋戬,史忠植.一种新的快速计算正区域的方法.计算机研究与发展, 2003, 40(5): 637-642. (LIU S H, SHENG Q J, SHI Z Z. A New Method for Fast Computing Positive Region. Journal of Computer Research and Development, 2003, 40(5): 637-642.)
[16] QIAN Y H, LIANG J Y, PEDRYCZ W，et al. Positive Approximation: An Accelerator for Attribute Reduction in Rough Set Theory. Artificial Intelligence, 2010, 174(9/10): 597-618.
[17] 张文修,仇国芳.基于粗糙集的不确定决策.北京:清华大学出版社, 2005. (ZHANG W X, QIU G F. Uncertain Decision Making Based on Rough Sets. Beijing, China: Tsinghua University Press, 2005.)
[18] 翟俊海,刘博,张素芳.基于相对分类信息熵的进化特征选择算法.模式识别与人工智能, 2016, 29(8): 682-690. (ZHAI J H, LIU B, ZHANG S F. Feature Selection via Evolutionary Computation Based on Relative Classification Information Entropy. Pattern Recognition and Artificial Intelligence, 2016, 29(8): 682-690.)
[19] 姚晟,徐风,赵鹏,等.基于邻域量化容差关系粗糙集模型的特征选择算法.模式识别与人工智能, 2017, 30(5): 416-428. (YAO S, XU F, ZHAO P，et al. Feature Selection Algorithm Based on Neighborhood Valued Tolerance Relation Rough Set Mo del. Pattern Recognition and Artificial Intelligence, 2017, 30(5): 416-428.)
[20] TSANG E C C, CHEN D G, YEUNG D S. Approximations and Reducts with Covering Generalized Rough Sets. Computers and Mathematics with Applications, 2008, 56(1): 279-289.
[21] CHEN D G, WANG C Z, HU H Q. A New Approach to Attribute Reduction of Consistent and Inconsistent Covering Decision Systems with Covering Rough Sets. Information Sciences, 2007, 177(17): 3500-3518.
[22] WANG C Z, HE Q, CHEN D G，et al. A Novel Method for Attri bute Reduction of Covering Decision Systems. Information Sciences, 2014, 254: 181-196.
[23] 杨田.覆盖粗糙集约简理论及应用.博士学位论文.长沙：湖南大学, 2010. (YANG T. The Reduction Theory of Covering Rough Sets and Its Application. Ph.D. Dissertation. Changsha, China: Hunan University, 2010.)
[24] WANG C Z, SHAO M W, SUN B Q，et al.An Improved Attribute Reduction Scheme with Covering Based Rough Sets. Applied Soft Computing, 2015, 26: 235-243.
[25] LI F, YIN Y Q. Approaches to Knowledge Reduction of Covering Decision Systems Based on Information Theory. Information Sciences, 2009, 179(11): 1694-1704.
[26] ZHANG X, MEI C L, CHEN D G,et al. Multi confidence Rule Acquisition Oriented Attribute Reduction of Covering Decision Systems via Combinatorial Optimization. Knowledge Based Systems, 2013, 50: 187-197.
[27] CHEN D G, LI W L, ZHANG X，et al. Evidence Theory Based Numerical Algorithms of Attribute Reduction with Neighborhood Covering Rough Sets. International Journal of Approximate Reasoning, 2014, 55(3): 908-923.
[28] TAN A H, LI J J, LIN G P，et al. Fast Approach to Knowledge Acquisition in Covering Information Systems Using Matrix Operations. Knowledge Based Systems, 2015, 79: 90-98.
[29] TAN A H, LI J J, LIN Y J，et al. Matrix Based Set Approximations and Reductions in Covering Decision Information Systems. International Journal of Approximate Reasoning, 2015, 59: 68-80.
[30] CHEN J K, LIN Y J, LIN G P，et al. Attribute Reduction of Covering Decision Systems by Hypergraph Model. Knowledge Based Systems, 2017, 118: 93-104.
[31] ZHANG Y L, LI J J. The Relative Reduction of Covering Genera lized Rough Sets // Proc of the IEEE International Conference on Granular Computing. Washington, USA: IEEE, 2008: 809-812.
[32] 张燕兰,李进金.覆盖决策系统的相对约简.工程数学学报, 2009, 26(5): 929-935. (ZHANG Y L, LI J J. On Relative Reduction of Knowledge in Covering Decision Systems. Chinese Journal of Engineering Mathematics, 2009, 26(5): 929-935.)
[33] DEMPSTER A P. Upper and Lower Probabilities Induced by a Multivalued Mapping. Annals of Mathematical Statistics, 1967, 38(2): 325-339.
[34] SHAFER G. A Mathematical Theory of Evidence. Princeton, USA：Princeton University Press, 1976.
[35] PAWLAK Z. Rough Probability. Bulletin of the Polish Academy of Science, 1984, 32: 607-615.
[36] SKOWRON A, GRZYMALA BUSSE J. From Rough Set Theory to Evidence Theory // YAGER R R, FEDRIZZI M, KACPRZYK J, eds. Advance in the Dempster Shafer Theory of Evidence. New York, USA: Wiley, 1994: 193-236.
[37] LIN G P, LIANG J Y, QIAN Y H. An Information Fusion Approach by Combining Multigranulation Rough Sets and Evidence Theory. Information Sciences， 2015， 314： 184-199.
[38] YAO Y Y, LINGRAS P J. Interpretations of Belief Functions in the Theory of Rough Sets. Information Sciences, 1998, 104（1/2）: 81-106.
[39] WU W Z, LEUNG Y, ZHANG W X. Connections between Rough Set Theory and Dempster Shafer Theory of Evidence. International Journal of General Systems, 2002, 31(4): 405-430.
[40] WU W Z, ZHANG M, LI H Z，et al. Knowledge Reduction in Random Information Systems via Dempster Shafer Theory of Evidence. Information Sciences, 2005, 174（3/4）: 143-164.
[41] 方连花,李克典.随机覆盖目标信息系统的属性约简.计算机工程与应用, 2014, 50(2): 107-111. (FANG L H, LI K D. Attribute Reduction in Random Covering Objective Information System. Computer Engineering and Applications, 2014, 50(2): 107-111.)
[42] QIN K Y, GAO Y, PEI Z. On Covering Rough Sets // Proc of the 2nd International Conference on Rough Sets and Knowledge Technology. Berlin, Germany: Springer, 2007: 34-41.
[43] ZHU W. Topological Approaches to Covering Rough Sets. Information Sciences, 2007, 177(6): 1499-1508.
[44] YAO Y Y, YAO B X. Covering Based Rough Set Approximations. Information Sciences, 2012, 200: 91-107.
[45] ZHANG Y L, LUO M K. Relationships between Covering Based Rough Sets and Relation Based Rough Sets. Information Sciences, 2013, 225: 55-71.
[46] ZHANG Y L, LI C Q, LIN M L，et al. Relationships between Generalized Rough Sets Based on Covering and Reflexive Neighborhood System. Information Sciences, 2015, 319: 56-67.
[47] CHEN D G, ZHANG X X, LI W L. On Measurements of Covering Rough Sets Based on Granules and Evidence Theory. Information Sciences, 2015, 317: 329-348.