基于CBR的智能决策支持系统研究与应用
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摘要
随着人工智能技术的不断发展,机器学习、数据挖掘、粗糙集、证据理论等理论方法的不断深入和完善,使智能决策支持系统的体系结构和智能化程度得到了较大的提高。然而随着Internet的普及应用,人们所掌握信息数据数量的剧增,给决策支持提供了丰富的信息资源和方便的互动交流平台,也使得更多的专家可以参与决策。基于智能技术的决策系统研究已经成为当前一个热点研究领域。
目前智能决策支持系统研究面临的主要问题之一为:越来越多半结构化、非结构化的、不确定的和相关的信息影响决策,决策专家很难凭借大脑的知识和经验准确、全面和快速地解决、分析信息,形成决策方案,而需要利用智能技术来辅助决策问题求解。
本文在分析目前智能决策支持系统现状和存在问题基础上,将基于案例推理的技术与智能决策支持系统相结合,提出了基于CBR的智能决策支持系统,并在法律咨询领域得到实际应用。采用基于事例推理(CBR)的方法,对事例表示、检索推理及启发式学习进行了研究,建立了基于CBR的法律咨询系统,并进行了实例分析,证明了CBR预测的正确性。
Recently, the architecture of intelligent decision support system has been greatly improved when artificial intelligence, including machine learning, data mining, rough set theory, Dumpster-Shafer theory and so on, was developed rapidly. At the end of last century and the very beginning of this century, we can acquire more and more information with the popularization of Internet, and Plenty of information and convenient communication platform are provided, and more experts can participate in decision activities. Research on intelligent decision theory and methods nowadays become an active research area.
Currently, one of the key problems of research on intelligent decision theory and methods mainly include: a mass of semi-structured, unstructured, uncertain and correlative information will affect decision. Experts hardly exactly, roundly and fast grasp and analyze all information by the knowledge and experience buried in their mind, and need intelligent methods to help resolving decision Problem, and then form a decision opinion.
This paper investigates and analyzes the research about intelligent decision support system, then discusses the application of CBR in IDSS and its key technique. This paper adopts the method Case-Based Reasoning(CBR), studies on the case reasoning、retrieval reasoning and learning, forwards the legal advisory system based on CBR, demonstrate of the CBR technology for successfully utilizing existing expertise to solve the complex problem.
目前智能决策支持系统研究面临的主要问题之一为:越来越多半结构化、非结构化的、不确定的和相关的信息影响决策,决策专家很难凭借大脑的知识和经验准确、全面和快速地解决、分析信息,形成决策方案,而需要利用智能技术来辅助决策问题求解。
本文在分析目前智能决策支持系统现状和存在问题基础上,将基于案例推理的技术与智能决策支持系统相结合,提出了基于CBR的智能决策支持系统,并在法律咨询领域得到实际应用。采用基于事例推理(CBR)的方法,对事例表示、检索推理及启发式学习进行了研究,建立了基于CBR的法律咨询系统,并进行了实例分析,证明了CBR预测的正确性。
Recently, the architecture of intelligent decision support system has been greatly improved when artificial intelligence, including machine learning, data mining, rough set theory, Dumpster-Shafer theory and so on, was developed rapidly. At the end of last century and the very beginning of this century, we can acquire more and more information with the popularization of Internet, and Plenty of information and convenient communication platform are provided, and more experts can participate in decision activities. Research on intelligent decision theory and methods nowadays become an active research area.
Currently, one of the key problems of research on intelligent decision theory and methods mainly include: a mass of semi-structured, unstructured, uncertain and correlative information will affect decision. Experts hardly exactly, roundly and fast grasp and analyze all information by the knowledge and experience buried in their mind, and need intelligent methods to help resolving decision Problem, and then form a decision opinion.
This paper investigates and analyzes the research about intelligent decision support system, then discusses the application of CBR in IDSS and its key technique. This paper adopts the method Case-Based Reasoning(CBR), studies on the case reasoning、retrieval reasoning and learning, forwards the legal advisory system based on CBR, demonstrate of the CBR technology for successfully utilizing existing expertise to solve the complex problem.
引文
[1]S.H.Liao.Expert system methodologies and applications--a decade review from 1995 to 2004[J].Expert systems with Applications.2005(28):93-103.
[2]周恺波.面向应用需求的基于案例推理方法与关键技术研究[D].华中科技大学系统工程研究所博士学位论文,2003.
[3]Hiroya Inakoshi,Seishi Okamoto,Yuiko Ohta,et al.Effective decision support for product configuration by using CBR.Fujitsu Laboratories LTD,Technical Report,2001.
[4]史忠植.知识发现[M].北京:清华大学出版社,2002.
[5]史忠植.智能主体及其应用[M].北京:科学出版社,2000.
[6]刘大有,赵宇霆,艾景军.基于事例的推理系统[C].见:陆汝铃.世纪之交的知识工程与知识科学[C].北京:清华大学出版社,2001:313-338.
[7]Maintaining Case-Based Reasoning Systems Using Fuzzy Decision Trees,C.K.Shiu,C.H.Sun,X.Z Wang,in Proceedings Advances in Case-Based Reasoning,LNAI,5th Europe Workshop,EWCBR 2000,Italy,2000:285-296.
[8]Transferring Case Knowledge to Adaptation Knowledge:An Approach for Case-Base Maintenance,C.K.Shiu,C.H.Sun,D.S Yeuang and X.Z Wang,an international journal "Computational Intelligence",May,2001.
[9]杨瑾,尤建新.基于案例推理的供应商决策支持系统研究[J].计算机工程与应用,2006,42(6):19-33.
[10]朱群雄,刘光.CBR技术在Multi-Agent故障诊断中的应用[J].计算机工程与应用,2004,40(21):111-113.
[11]HU WEN-BIN,WANG SHAO-MEI,PAN WEN-JUN.Research and implement of case-base reasoning in online logistics resource decision[J].Journal of Wuhan University of Technology,2003,27(4):581-584.
[12]Morton M S S.Management decision support:computer based support for decision making[M].Division of Research,Harvard university,Cambridge Mass,1971.
[13]Keen P G M,Morton M S.Decision support system[M].MIS Quartenly,1978.
[14]俞瑞钊,陈奇.智能决策支持系统实现技术[M].杭州:浙江大学出版社,2000.
[15]Schank R.Dynamic Memory:A Theory of Learning in Computers and People[M].New York:Cambridge University Press,1982.
[16]C.K.Riesbeck,R.C.Schank.Inside Case-Based Reasoning,Lawrence Erlbaum Associates,Pub.,Hillsdale,989.
[17]Kolodner,J.Case-Based Reasoning.Morgan Kaufmann Publishers,Inc.,1993
[18]WATSON I.Applying case- based reasoning:techniques for enterprise system[M])San Francisco,CA:Morgan Kaufmann,1997.
[19]杨善林.智能决策方法与智能决策支持系统[M].北京:科学出版社.2005.
[20]Mark W,Simoudis E,Hinkle D.Case-based Reasoning:Expectations and Results.Case-Based Reasoning:Experiences,Lessons & Future Directions,1996:167-294 MA,AAAI Press/MIT Press.
[21]张荣梅.智能决策支持系统研究丌发及应用[M].北京:冶会工业出版社.2003.
[22]A.R.Golding,RS.Renbloom.Improving rule-based systems through case-based reasoning.Proceedings of AAAI'91,MIT Press,2-27.
[23]K.Hanney and M.Keane.Learning adaptation rules from a case base.In Proceedings of the Third European Workshop on Case-based Reasoning,Lausanne,1996,178-192.
[24]Hiroaki Kitano,Hideo Shimazu,Hihiro Shibata.Case-Method:A methodology for building large-scale case-based systems.In:Proceedings of AAAI-93,303-308.
[25]Jagielska L,Matthews C,Whitfort T.An investigation into the application of neural networks,fuzzy logic,genetic algorithms,and rough sets to automated knowledge acquisition for classification problems.Neurocomputing,24,1999,37-54.
[26]John.Sbreese,David,Heckerman.Decision-theoretic case-based reasoning[A].In Proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics[C],56-63,1995.
[27]杨斌宇.基于案例的推理在智能决策支持系统中的应用[D].吉林大学硕士学位论文,2004.
[28]王宗军.基于知识的综合评价问题的模糊推理求解方法[J].系统工程学报,1998,13(1).
[29]顾培亮,王勐.运用“思想库”和“案例库”对决策进行扩展支持的研究[J].系统工程学报,1995,10(2).
[30]张维,黄爱民.一种基于案例库的专家选择支持系统[J].决策与决策支持系统,1994,4(3):1-7.
[31]Sharma S,Sleeman,D Refiner.A Case based Differential Diagnosis Aide for knowledge Acquisition and Knowledge Refinement.EWSL 88,Proceedings of the Third European Working Session on Learning Pitman,1998.201-210.
[32]Watson I.Applying Case-Based Reasoning:Techniques for Enterprise Systems[M].Morgan Kaufmann Publishers Inc.,1997.
[33]Doyle M.,Hayes C.,Cunningham,P.and Smith,B.CBR Net:Smart Technology over a Network.Department of Computer Science,Trinity College Dublin,1998.
[34]W.Liao,Z.Zhang,C.Mount.Similarity Measures for Retrieval in Case-based Reasoning Systems[J].Applied Artificial Intelligence,1998,12:267-288.
[35]刘缵敏,孙义,史忠植.CBR检索的线性回归模型及实现[J].计算机工程,2007,33(4):165-167.
[36]李海林,柳柄祥.一种基于模糊集的案例推理方法[C].2007中国控制与决策学术年会论文集,2007,704-707.
[37]李建洋.基于粗糙集的案例推理智能决策支持系统的研究[D].安徽大学硕士学位论文,2003.
[38]杨振刚.CBR-ANN智能决策支持方法及应用[D].华南理工大学博士学位论文,2007.
[39]赵鹏,蔡庆生,耿焕同,于琨.基于商空间模型的CBR系统[J].计算机工程,2006,32(24):162-163.
[40]蒋国瑞,赵新竹.基于案例推理与Mutli-Agent的TBT预警系统研究[J].计算机工程与应用,2006,42(6):199-201.
[2]周恺波.面向应用需求的基于案例推理方法与关键技术研究[D].华中科技大学系统工程研究所博士学位论文,2003.
[3]Hiroya Inakoshi,Seishi Okamoto,Yuiko Ohta,et al.Effective decision support for product configuration by using CBR.Fujitsu Laboratories LTD,Technical Report,2001.
[4]史忠植.知识发现[M].北京:清华大学出版社,2002.
[5]史忠植.智能主体及其应用[M].北京:科学出版社,2000.
[6]刘大有,赵宇霆,艾景军.基于事例的推理系统[C].见:陆汝铃.世纪之交的知识工程与知识科学[C].北京:清华大学出版社,2001:313-338.
[7]Maintaining Case-Based Reasoning Systems Using Fuzzy Decision Trees,C.K.Shiu,C.H.Sun,X.Z Wang,in Proceedings Advances in Case-Based Reasoning,LNAI,5th Europe Workshop,EWCBR 2000,Italy,2000:285-296.
[8]Transferring Case Knowledge to Adaptation Knowledge:An Approach for Case-Base Maintenance,C.K.Shiu,C.H.Sun,D.S Yeuang and X.Z Wang,an international journal "Computational Intelligence",May,2001.
[9]杨瑾,尤建新.基于案例推理的供应商决策支持系统研究[J].计算机工程与应用,2006,42(6):19-33.
[10]朱群雄,刘光.CBR技术在Multi-Agent故障诊断中的应用[J].计算机工程与应用,2004,40(21):111-113.
[11]HU WEN-BIN,WANG SHAO-MEI,PAN WEN-JUN.Research and implement of case-base reasoning in online logistics resource decision[J].Journal of Wuhan University of Technology,2003,27(4):581-584.
[12]Morton M S S.Management decision support:computer based support for decision making[M].Division of Research,Harvard university,Cambridge Mass,1971.
[13]Keen P G M,Morton M S.Decision support system[M].MIS Quartenly,1978.
[14]俞瑞钊,陈奇.智能决策支持系统实现技术[M].杭州:浙江大学出版社,2000.
[15]Schank R.Dynamic Memory:A Theory of Learning in Computers and People[M].New York:Cambridge University Press,1982.
[16]C.K.Riesbeck,R.C.Schank.Inside Case-Based Reasoning,Lawrence Erlbaum Associates,Pub.,Hillsdale,989.
[17]Kolodner,J.Case-Based Reasoning.Morgan Kaufmann Publishers,Inc.,1993
[18]WATSON I.Applying case- based reasoning:techniques for enterprise system[M])San Francisco,CA:Morgan Kaufmann,1997.
[19]杨善林.智能决策方法与智能决策支持系统[M].北京:科学出版社.2005.
[20]Mark W,Simoudis E,Hinkle D.Case-based Reasoning:Expectations and Results.Case-Based Reasoning:Experiences,Lessons & Future Directions,1996:167-294 MA,AAAI Press/MIT Press.
[21]张荣梅.智能决策支持系统研究丌发及应用[M].北京:冶会工业出版社.2003.
[22]A.R.Golding,RS.Renbloom.Improving rule-based systems through case-based reasoning.Proceedings of AAAI'91,MIT Press,2-27.
[23]K.Hanney and M.Keane.Learning adaptation rules from a case base.In Proceedings of the Third European Workshop on Case-based Reasoning,Lausanne,1996,178-192.
[24]Hiroaki Kitano,Hideo Shimazu,Hihiro Shibata.Case-Method:A methodology for building large-scale case-based systems.In:Proceedings of AAAI-93,303-308.
[25]Jagielska L,Matthews C,Whitfort T.An investigation into the application of neural networks,fuzzy logic,genetic algorithms,and rough sets to automated knowledge acquisition for classification problems.Neurocomputing,24,1999,37-54.
[26]John.Sbreese,David,Heckerman.Decision-theoretic case-based reasoning[A].In Proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics[C],56-63,1995.
[27]杨斌宇.基于案例的推理在智能决策支持系统中的应用[D].吉林大学硕士学位论文,2004.
[28]王宗军.基于知识的综合评价问题的模糊推理求解方法[J].系统工程学报,1998,13(1).
[29]顾培亮,王勐.运用“思想库”和“案例库”对决策进行扩展支持的研究[J].系统工程学报,1995,10(2).
[30]张维,黄爱民.一种基于案例库的专家选择支持系统[J].决策与决策支持系统,1994,4(3):1-7.
[31]Sharma S,Sleeman,D Refiner.A Case based Differential Diagnosis Aide for knowledge Acquisition and Knowledge Refinement.EWSL 88,Proceedings of the Third European Working Session on Learning Pitman,1998.201-210.
[32]Watson I.Applying Case-Based Reasoning:Techniques for Enterprise Systems[M].Morgan Kaufmann Publishers Inc.,1997.
[33]Doyle M.,Hayes C.,Cunningham,P.and Smith,B.CBR Net:Smart Technology over a Network.Department of Computer Science,Trinity College Dublin,1998.
[34]W.Liao,Z.Zhang,C.Mount.Similarity Measures for Retrieval in Case-based Reasoning Systems[J].Applied Artificial Intelligence,1998,12:267-288.
[35]刘缵敏,孙义,史忠植.CBR检索的线性回归模型及实现[J].计算机工程,2007,33(4):165-167.
[36]李海林,柳柄祥.一种基于模糊集的案例推理方法[C].2007中国控制与决策学术年会论文集,2007,704-707.
[37]李建洋.基于粗糙集的案例推理智能决策支持系统的研究[D].安徽大学硕士学位论文,2003.
[38]杨振刚.CBR-ANN智能决策支持方法及应用[D].华南理工大学博士学位论文,2007.
[39]赵鹏,蔡庆生,耿焕同,于琨.基于商空间模型的CBR系统[J].计算机工程,2006,32(24):162-163.
[40]蒋国瑞,赵新竹.基于案例推理与Mutli-Agent的TBT预警系统研究[J].计算机工程与应用,2006,42(6):199-201.