在线阅读 --自然科学版 2020年4期《基于决策属性粒度树提取决策规则》
基于决策属性粒度树提取决策规则--[在线阅读]
赵思雨1,2, 钱婷2,3, 宋笑雪4
1. 咸阳师范学院 数学与信息科学学院, 陕西 咸阳 712000;
2. 西北大学 概念认知与智能研究中心, 陕西 西安 710127;
3. 西安石油大学 理学院, 陕西 西安 710065;
4. 咸阳师范学院 计算机学院, 陕西 咸阳 712000
起止页码: 288--294页
DOI: 10.13763/j.cnki.jhebnu.nse.2020.04.002
摘要
粒计算通过粒的形成、粒的转移、粒的合成与分解等手段有效地解决问题.利用属性粒度树,将粒计算与决策形式背景的规则提取理论相结合.首先将决策属性进行粒化,给出多粒度决策形式背景的定义;其次研究了粒化前后决策形式背景协调性的关系;最后在假设粒化前后决策形式背景协调的前提下,研究了粒化前后决策规则之间的关系.

Extraction of Decision Rules Based on Granularity Tree of Decision Attributes
ZHAO Siyu1,2, QIAN Ting2,3, SONG Xiaoxue4
1. College of Mathematics and Information Science, Xianyang Normal University, Shaanxi Xianyang 712000, China;
2. Institute of Concepts Cognition and Intelligence, Northwest University, Shaanxi Xi'an 710127, China;
3. College of Science, Xi'an Shiyou University, Shaanxi Xi'an 710065, China;
4. School of Computer Science, Xianyang Normal University, Shaanxi Xianyang 712000, China
Abstract:
Granular computing is well known for formation of granule,transformation of granule,synthesis and decomposition of granule.It is very meaningful to combine granular computing with rule extraction theory of decision formal context by using attribute granularity tree.Firstly,we granulate decision attributes and define the multiple granularity decision formal context.Secondly,the relationship between the coordination of decision formal context before and after granulation is studied.Lastly, the relationship between decision rules of before and after granulation are given based on the consistent decision formal context.

收稿日期: 2019-09-12
基金项目: 国家自然科学基金(11801440,61772021,61472471);陕西省自然科学基础研究计划项目(2019JQ-816);陕西省教育厅科研计划项目(19JK0929)

参考文献:
[1]WEI Ling,QI Jianjun,ZHANG Wenxiu.Attribute Reduction Theory of Concept Lattice Based on Decision Formal Contexts[J].Science in China Series F:Information Sciences,2008,51(7):910-923.doi:10.1007/s11432-008-0067-4
[2]LI J H,MEI C L,LYU Y J.Incomplete Decision Contexts:Approximate Concept Construction,Rule Acquisition and Knowledge Reduction[J].International Journal of Approximate Reasoning,2013,54(1):149-165.doi:10.1016/j.ijar.2012.07.005
[3]LI J H,MEI C L,WANG J H,et al.Rule-preserved Object Compression in Formal Decision Contexts Using Concept Lattices[J].Knowledge-based Systems,2014,71:435-445.doi:10.1016/j.knosys.2014.08.020
[4]张清华,王国胤,刘显全.基于最大粒的规则获取算法[J].模式识别与人工智能,2012,25(3):388-396.doi:10.1645l/j.cnki.issn.1003-6059.2012.03.022. ZHANG Qinghua,WANG Guoyin,LIU Xianquan.Rule Acquisition Algorithm Based on Maximal Granule[J].Pattern Recognition and Aitificial Intelligence, 2012,25(3):388-396.
[5]朱治春,魏玲.基于类背景的双向规则的获取[J].西北大学学报(自然科学版),2015,45(4):517-524.doi:10.16152/j.cnki.xdxbzr.2015-04-001. ZHU Zhichun,WEI Ling.Two-way Rules Acquisition Based on Class Context[J].Journal of Northwest University(Natural Science),2015,45(4):517-524.
[6]ZADEH L.Toward a Theory of Fuzzy Information on Granulation and Its Centrality in Human Reasoning and Fuzzy Logic[J].Fuzzy Sets and Systems,1997,90(2):111-127.doi:10.1016/s0165.0114(97)00077-8
[7]WU W Z,LEUNG Y,MI J S.Granular Computing and Knowledge Reduction in Formal Contexts[J].IEEE Transactions on Knowledge and Date Engineering,2009,21(10):1461-1474.doi:10.1109/tkde.2008.223
[8]万青,马盈仓.基于属性概念的决策形式背景协调性研究[J].西北大学学报(自然科学版),2017,47(3):336-341.doi:10.16152/j.cnki.xdxbzr.2017-03-004 WAN Qing,MA Yingcang.A Study of Formal Context' Consistency Based on Attribute Concepts[J].Journal of Northwest University(Natural Science),2017,43(3):336-341.
[9]ZHI H L,LI J H.Granule Description Based on Formal Concept Analysis[J].Knowledge-based Systems,2016,104:62-73.doi:10.1016/j.knosys.2016.04.011
[10]QI J J,WEI L,WAN Q.Multi-level Granularity in Formal Concept Analysis[J].Granular Computing,2019,4(3):351-362.doi.10.1007/s41066-018-0112-7
[11]WU W Z,LEUNG Y.Theory and Applications of Granular Labeled Partitions in Multi-scale Decision Tables[J].Information Sciences,2011,181:3878-3897.doi:10.1016/j.ins.2011.04.047
[12]李金海,吴伟志.形式概念分析的粒计算方法及其研究展望[J].山东大学学报(理学版),2017,52(7):1-12.doi:106040/j.issn.1671-9352.0.2016279 LI Jinhai,WU Weizhi.Granular Computing Approach for Formal Concept Analysis and Its Research Outlooks[J].Journal of Shandong University(Natural Science),2017,52(7):1-12.
[13]XIE J P,YANG M H,LI J H,et al.Rule Acquisition and Optimal Scale Selection in Multi-scale Formal Decision Contexts and Their Applications to Smart City[J].Future Generation Computer Systems,2018,83:564-581.doi:10.10160/j.future.2017.03.011
[14]BELOHLAVEK R,BAETS B D,KONECNY J.Granularity of Attributes in Formal Concept Analysis[J].Information Sciences,2014,260:149-170.doi:10.1016/j.ins.2013.10.021
[15]曾望林,折延宏.面向对象的多粒度形式概念分析[J].计算机科学,2018,45(10):51-53.doi:10.11896/j.issn.102-137X.2018.10.010 ZENG Wanglin,SHE Yanhong.Object-oriented Multigranulation Formal Concept Analysis[J].Computer Science,2018,45(10):51-53.
[16]李金海,吴伟志,邓硕.形式概念分析的多粒度标记理论[J].山东大学学报(理学版),2019,54(2):1-11.doi:10.6040/j.issn.1671-9352.9.2018.002 LI Jinhai,WU Weizhi,DENG Shuo.Multi-scale Theory in Formal Concept Analysis[J].Journal of Shandong University (Natural Science),2019,54(2):1-11.
[17]WILLE R.Restructuring Lattice Theory:An Approach Based on Hierarchies of Concepts[C].//RIVAL I.Ordered Sets,Reidel:Dordrecht-Boston,1982:445-470.
[18]张文修,仇国芳.基于粗糙集的不确定决策[M].北京:清华大学出版社,2005. ZHANG Wenxiu,QIU Guofang.Uncertain Decision Making Based on Rough Sets[M].Beijing:Tsinghua Universiy Press,2005.