Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Strategic Study of CAE >> 2002, Volume 4, Issue 3

All Set and Artificial Intelligence

Northern Jiaotong University, Beijing 100044, China

Funding project:"八六三"高技术研究发展计划资助项目(863-306 ZD06-03-6) Received: 2001-10-25 Revised: 2001-11-12 Available online: 2002-03-20

Next Previous

Abstract

This paper presents a brand new set theory, All Set theory, which is the united set form of the current set theories including crisp set, fuzzy set, extension set, vague set, rough set, set pair analysis, FHW (fuzzy gray matter - element),FEEC(fuzzy extension economic control) and so on. The operation of the all set is also discussed in detail. A kind of style of the human being' s intelligence can be described by a kind of set form, thus all set is the united form. An all set is comprised of four parts, that is ( A, B, F, J ). A is the universe of the problem discussed. One of the elements in A can be described by an element of B. F is the map from A to B. And J restricts F. From this model, the concept of subjection that is the basic conception of human´s intelligence can be simulated. Hence the wide application of all set theory in the field of artificial intelligence including pattern recognition, clustering, logic, machine learning, intelligent decision, etc. , can be developed. Especially the relation among all set, logic and human intelligence style is illustrated in the paper. The theory of all set can not only unify and summarize the current theories but also provide the primary method for establishing new set theory and new logic.

Figures

图1

图10

图2

图3

图4

图5

图6

图7

图8

图9

References

[ 1 ] 曹鸿兴.系统周界的一般理论———界壳论[M ].北京:气象出版社, 1997

[ 2 ] 徐浩磐, 惠永涛, 宋方敏.离散数学及其在计算机中的应用[M ].北京:人民邮电出版社, 1997 link1

[ 3 ] ZadehLA .Fuzzysets, inform[J].Control, 1965, (8) :338~353

[ 4 ] 蔡 文.物元模型及其应用[M ].北京:科学技术文献出版社, 1994 link1

[ 5 ] GauWenlung, BuehrerDJ.Vaguesets[J].IEEETransactiononSystem, Manandcybernetic, 1993, 23 (2) :610~615

[ 6 ] 贺仲雄, 隋志强.模糊灰色物元空间决策系统[J].系统工程与电子技术, 1986, (7) :1~11 link1

[ 7 ] 贺仲雄, 魏小涛.模糊可拓经济控制[J].北方交通大学学报, 1996, (3) :657~661 link1

[ 8 ] 赵克勤.集对分析及其应用[M].杭州:浙江科学技术出版社, 2000 link1

[ 9 ] PawlakZ .Roughset[J].IntlJofInformationandComputerScience, 1982, (11) :341~365 link1

[10] BanerjeeM .Roughnessofafuzzyset[J].InformationSciences, 1996, 93 (1) :23~29

[11] 曾黄麟.粗集理论及其应用———关于数据推理的新方法[M ].重庆:重庆大学出版社, 1996

[12] 张文修, 吴伟志, 梁吉业, 等.粗糙集合理论与方法[M].北京:科学出版社, 2001

[13] 史忠植.高级人工智能[M ].北京:科学出版社, 1998 link1

[14] 边肇祺, 张学工.模式识别[M].北京:清华大学出版社, 2001

[15] 贺仲雄.模糊数学及其应用[M ].天津:天津出版社, 1983

[16] 陆汝铃.世纪之交的知识工程与知识科学[M ].北京:清华大学出版社, 2001.289~291

[17] Slavka, Bodjanova.Approximationoffuzzyconceptsindecisionmaking[J].FuzzySetsandSystems, 1997, 85:23~29

[18] 马志峰, 邢汉承, 郑晓妹.不完整Vague决策表中的近似集合学习方法[J].计算机研究与进展, 2000, (9) :1050~1057 link1

[19] ZhangWanjun, WangZhenyu, ZhaoYi, etal.Onfuzzyextensiondecisionsystemofthelarge scalesystem[A ].WCICA2000Proceedingsofthe3rdWorldCongressonIntelligentControlandAutomation[C], 2000

[20] 李 华, 刘 峰, 贺仲雄.多维界壳约束下的模糊可拓经济控制[J].中国工程科学, 2001, 3 (8) :52~57 link1

Related Research