基于聚类算法的多属性复杂大群体决策方法研究
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摘要
多属性复杂大群体决策(Multi-attribute Complex Huge Group-decision，MCHGD)作为一种决策领域新的发展趋势，越来越被理论界和实业界所重视，它迫切需要相应决策方法来提供支持。因此，本文将从新的角度并基于聚类算法来研究多属性复杂大群体决策方法。
本文研究的群体复杂性主要体现在：复杂群体行为对群决策的影响、多方案群决策评判准则权重的确定、个体意见发散的一致性修正等，针对考虑以上群体复杂性的大群体高效集结，本文设计了一种改进的聚类算法(Minimum Fuzzy C-means，MFCM)，并提出了基于此算法的具有复杂群体行为的大群体决策方法、基于此算法及优化硬C-均值聚类算法(Weighted Hard C-means，WHCM)的群体一致性修正方法，同时还设计了基于多智能体(Multi-agent)和数据仓库(Data Warehouse，DW)的多属性复杂大群体决策支持系统(Multi-attribute Complex Huge Group-decision Support System，MCHGDSS)框架结构，实现了其中基于聚类算法的MCHGDSS，最后对中国网络消费行为群体决策进行了实证研究。
本文主要的研究成果如下：
(1)提出了一种改进的聚类算法和基于此算法的具有复杂群体行为的大群体决策方法。本文提出一种将多种复杂群体行为对群决策的影响和大群体高效集结综合考虑的两阶段群体决策理论和方法。第一阶段为群体思维交互决策，通过设计群体思维的五阶段发展过程和基于民主型领导控制的多维空间冲突协调机制来控制复杂群体行为对群决策结果的影响；同时，为更好描述群体成员之间的关系，将群体成员视为一张图，用邻接矩阵表示成员之间的关系，应用MFCM中的全部最小连通支配集算法(Minimum Connected Donating Set Algorithm，MCDSA)得到控制整个群体的民主型领导成员集。第二阶段是群体集结，借助群体思维交互结果，将MFCM继续应用于多属性复杂大群体决策中，能有效解决600个以上成员的集结。接着，本文还定义了群体偏好矢量和群体一致性指标等概念，利用熵权法得到多方案群决策评判准则权重，给出多属性复杂大群体决策结果，最后通过计算机仿真实验和与其它方法的对比分析验证了该方法的有效性和正确性。
作为以上新方法的技术基础，本文针对传统模糊C-均值聚类算法(Puzzy C-means，甽中存在的大数据量算法耗时和局部极值等问题，结合图论中最小连通支配集理论给出了一种新的聚类算法MFCM。改进的MFCM算法一方面可以辅助大规模群体集结，另方面由于采用了图论理论，可从关联、控制的角度较好描述复杂群体行为对群决策的影响。
(2)提出了基于聚类算法的群体一致性修正方法。针对某个决策方案，本文从新的角度提出了一种基于聚类算法、且能面向较大规模群体、考虑成员学习进化能力并有效收敛群体意见的群体一致性修正方法。本文认为群体一致性修正是一个包含多轮决策过程的不断进化过程，并设计了群体成员学习进化决策程序；接着，利用群体成员相似性和群体一致性的紧密关系，借助一种能够处理大数据量聚类的C-均值类型聚类算法，通过梯度下降法以逐步优化属性权重，并逐渐修正群体一致性来避免因个别成员意见偏离太大而引起的群决策失误；最后通过计算机仿真和实验对比分析验证了该方法的正确、有效性。经过群体一致性修正后，可继续利用基于聚类算法的具有复杂群体行为的大群体决策方法进行决策。
(3)提出了一种新的数据挖掘关联算子模型。分布、异构式的多属性复杂大群体决策支持系统需要利用数据挖掘手段获取面向主题的、概括和聚集的信息，本文基于Anindya Datta等提出的一种实现数据挖掘分析的代数模型，通过增加新的关联算子在跨多个多维立方体的分析方面拓展了这个模型。
As a new development trend in decision field, the MCHGD (Multi-attribute Complex Huge Group-decision) is accounted by Theory and Business Career, it urgently demands proper decision methods to support the decision processes. Therefore, this thesis will study the methods of MCHGD basing on the clustering algorithm in a different light.
According to the problems of group-complexity such as the influence of decision results imposed by complex group-behaviors, the verifying of the weight of alternative group-decision evaluation criteria, and the group-consistency amendment of individual' s divergence of their owns, in addition, the problem of huge group's high efficiency aggregation considering complex group characteristics, this thesis outlines the improved MFCM (Minimum Fuzzy c-means) basing on the Graph Theory, and proposes the huge group-decision method with the group-complexity basing on MFCM, the method of group-consistency amendment basing on MFCM and WHCM (Weighted Hard C-means). In the mean time, the thesis presents the framework of the MCHGDSS (Multi-attribute Complex Huge Group-decision Support System) basing on Multi-agent and DW (Data Warehouse), develops the MCHGDSS basing on the clustering algorithm among it. At last, a case research of the group-consume behavior decision of Chinese consumer in network economic environment is performed.
Main contents of this thesis are outlined as follows:
(1) An improved clustering algorithm and the efficient huge group-decision theory and method with complex group-behavior basing on the algorithm. To combine the group-thinking interaction decision with the efficient huge group-integration decision, the thesis points out a kind of 2-phase group-decision theory and method. First, to deal with the problems of decision quality caused by many kinds of complex group-behaviors, the thesis designs 5-phase development model of group-thinking, and the coordinating mechanism of multi-dimension supervised by the group-leaders which is introduced to control the process of group-thinking interaction. In the mean time, to describe the relations among the group-member, the thesis views the group-member as a picture, representing their relations by matrix adjacency, the democratic leaders' set is also produced by MFCM. And then the thesis aggregates the huge group efficiently using MFCM continuously, defines group-preference vector and group-consistency index. The result of MCHGD is put forward after getting the weight of alternative group-decision criteria using entropy method. The validity and accuracy of the method is verified by the computer simulation and comparing analysis.
As the technical basis of the above method, an improved MFCM is presented to support the MCHGD. To answer the questions of the existing fuzzy clustering algorithms involving local limit value, bad scalability and only for the statistic data, this thesis puts forward a new kind of MFCM basing on MCDSA (Minimum Connected Donating Set Algorithm) which clusters only the dominating points to improve the traditional FCM from the view of overall.
The improved MFCM could be used to aggregate the group, on the other hand, it also could be used to particular describe the influence of the complex group-behaviors from the point of correlation and control.
(2) A huge group-consistency amendment method with learning ability basing on clustering. According to a certain decision project, the thesis puts forward a group-consistency amendment method basing on a kind of optimized c-means clustering algorithm, aiming at lager scale group, and considering the ability of evolution by learning. First, the thesis regards the group-consistency amendment is an evolutionary process and designs the evolutionary program of the group-member. Then, by using the tightness relations of the group-comparability and the group-consistency, a gradual decision method of amendment group-consistency by optimizing attributes' weight is presented to avoid the fault caused by individual idea divergence. Lastly, the method is also validated by the computer simulation and comparing analysis. The above efficient huge group-decision theory and method with complex group-behavior could be used to make decision after the consistency amendment.
(3) A new DW associational operator model is brought forward. Because the MCHGDSS needs the general and assemble information to support its distribution, the thesis extends the DW analysis algebra model advanced by Datta, realizes the operations among multiple multi-dimensional cubes by adding a kind of new associational operator.
本文研究的群体复杂性主要体现在：复杂群体行为对群决策的影响、多方案群决策评判准则权重的确定、个体意见发散的一致性修正等，针对考虑以上群体复杂性的大群体高效集结，本文设计了一种改进的聚类算法(Minimum Fuzzy C-means，MFCM)，并提出了基于此算法的具有复杂群体行为的大群体决策方法、基于此算法及优化硬C-均值聚类算法(Weighted Hard C-means，WHCM)的群体一致性修正方法，同时还设计了基于多智能体(Multi-agent)和数据仓库(Data Warehouse，DW)的多属性复杂大群体决策支持系统(Multi-attribute Complex Huge Group-decision Support System，MCHGDSS)框架结构，实现了其中基于聚类算法的MCHGDSS，最后对中国网络消费行为群体决策进行了实证研究。
本文主要的研究成果如下：
(1)提出了一种改进的聚类算法和基于此算法的具有复杂群体行为的大群体决策方法。本文提出一种将多种复杂群体行为对群决策的影响和大群体高效集结综合考虑的两阶段群体决策理论和方法。第一阶段为群体思维交互决策，通过设计群体思维的五阶段发展过程和基于民主型领导控制的多维空间冲突协调机制来控制复杂群体行为对群决策结果的影响；同时，为更好描述群体成员之间的关系，将群体成员视为一张图，用邻接矩阵表示成员之间的关系，应用MFCM中的全部最小连通支配集算法(Minimum Connected Donating Set Algorithm，MCDSA)得到控制整个群体的民主型领导成员集。第二阶段是群体集结，借助群体思维交互结果，将MFCM继续应用于多属性复杂大群体决策中，能有效解决600个以上成员的集结。接着，本文还定义了群体偏好矢量和群体一致性指标等概念，利用熵权法得到多方案群决策评判准则权重，给出多属性复杂大群体决策结果，最后通过计算机仿真实验和与其它方法的对比分析验证了该方法的有效性和正确性。
作为以上新方法的技术基础，本文针对传统模糊C-均值聚类算法(Puzzy C-means，甽中存在的大数据量算法耗时和局部极值等问题，结合图论中最小连通支配集理论给出了一种新的聚类算法MFCM。改进的MFCM算法一方面可以辅助大规模群体集结，另方面由于采用了图论理论，可从关联、控制的角度较好描述复杂群体行为对群决策的影响。
(2)提出了基于聚类算法的群体一致性修正方法。针对某个决策方案，本文从新的角度提出了一种基于聚类算法、且能面向较大规模群体、考虑成员学习进化能力并有效收敛群体意见的群体一致性修正方法。本文认为群体一致性修正是一个包含多轮决策过程的不断进化过程，并设计了群体成员学习进化决策程序；接着，利用群体成员相似性和群体一致性的紧密关系，借助一种能够处理大数据量聚类的C-均值类型聚类算法，通过梯度下降法以逐步优化属性权重，并逐渐修正群体一致性来避免因个别成员意见偏离太大而引起的群决策失误；最后通过计算机仿真和实验对比分析验证了该方法的正确、有效性。经过群体一致性修正后，可继续利用基于聚类算法的具有复杂群体行为的大群体决策方法进行决策。
(3)提出了一种新的数据挖掘关联算子模型。分布、异构式的多属性复杂大群体决策支持系统需要利用数据挖掘手段获取面向主题的、概括和聚集的信息，本文基于Anindya Datta等提出的一种实现数据挖掘分析的代数模型，通过增加新的关联算子在跨多个多维立方体的分析方面拓展了这个模型。
As a new development trend in decision field, the MCHGD (Multi-attribute Complex Huge Group-decision) is accounted by Theory and Business Career, it urgently demands proper decision methods to support the decision processes. Therefore, this thesis will study the methods of MCHGD basing on the clustering algorithm in a different light.
According to the problems of group-complexity such as the influence of decision results imposed by complex group-behaviors, the verifying of the weight of alternative group-decision evaluation criteria, and the group-consistency amendment of individual' s divergence of their owns, in addition, the problem of huge group's high efficiency aggregation considering complex group characteristics, this thesis outlines the improved MFCM (Minimum Fuzzy c-means) basing on the Graph Theory, and proposes the huge group-decision method with the group-complexity basing on MFCM, the method of group-consistency amendment basing on MFCM and WHCM (Weighted Hard C-means). In the mean time, the thesis presents the framework of the MCHGDSS (Multi-attribute Complex Huge Group-decision Support System) basing on Multi-agent and DW (Data Warehouse), develops the MCHGDSS basing on the clustering algorithm among it. At last, a case research of the group-consume behavior decision of Chinese consumer in network economic environment is performed.
Main contents of this thesis are outlined as follows:
(1) An improved clustering algorithm and the efficient huge group-decision theory and method with complex group-behavior basing on the algorithm. To combine the group-thinking interaction decision with the efficient huge group-integration decision, the thesis points out a kind of 2-phase group-decision theory and method. First, to deal with the problems of decision quality caused by many kinds of complex group-behaviors, the thesis designs 5-phase development model of group-thinking, and the coordinating mechanism of multi-dimension supervised by the group-leaders which is introduced to control the process of group-thinking interaction. In the mean time, to describe the relations among the group-member, the thesis views the group-member as a picture, representing their relations by matrix adjacency, the democratic leaders' set is also produced by MFCM. And then the thesis aggregates the huge group efficiently using MFCM continuously, defines group-preference vector and group-consistency index. The result of MCHGD is put forward after getting the weight of alternative group-decision criteria using entropy method. The validity and accuracy of the method is verified by the computer simulation and comparing analysis.
As the technical basis of the above method, an improved MFCM is presented to support the MCHGD. To answer the questions of the existing fuzzy clustering algorithms involving local limit value, bad scalability and only for the statistic data, this thesis puts forward a new kind of MFCM basing on MCDSA (Minimum Connected Donating Set Algorithm) which clusters only the dominating points to improve the traditional FCM from the view of overall.
The improved MFCM could be used to aggregate the group, on the other hand, it also could be used to particular describe the influence of the complex group-behaviors from the point of correlation and control.
(2) A huge group-consistency amendment method with learning ability basing on clustering. According to a certain decision project, the thesis puts forward a group-consistency amendment method basing on a kind of optimized c-means clustering algorithm, aiming at lager scale group, and considering the ability of evolution by learning. First, the thesis regards the group-consistency amendment is an evolutionary process and designs the evolutionary program of the group-member. Then, by using the tightness relations of the group-comparability and the group-consistency, a gradual decision method of amendment group-consistency by optimizing attributes' weight is presented to avoid the fault caused by individual idea divergence. Lastly, the method is also validated by the computer simulation and comparing analysis. The above efficient huge group-decision theory and method with complex group-behavior could be used to make decision after the consistency amendment.
(3) A new DW associational operator model is brought forward. Because the MCHGDSS needs the general and assemble information to support its distribution, the thesis extends the DW analysis algebra model advanced by Datta, realizes the operations among multiple multi-dimensional cubes by adding a kind of new associational operator.
引文
[1] 徐选华，陈晓红．基于矢量空间的群体聚类方法研究[J]．系统工程与电子技术，2005，27(6)：1034～1037
[2] 高新波．模糊聚类分析及其应用[M]．西安：西安电子科技大学出版社，2004．39～69
[3] Zadeh L A. Fuzzy Logic[J]. IEEE Trans on Control System Magazine, 1988, 11(15): 83～93
[4] 朱剑英．应用模糊数学方法的若干问题及处理方法[J]．模糊系统与数学，1992，11(2)：57～63
[5] Yu J , Huang Hk A New Weighting Fuzzy C-Means Algorithms[A]. Proceedings of the 12th IEEE Conf on Fuzzy Systems[C]. Louis, 2003. 896～901
[6] Yu J. On the Fuzziness Index of the FCM Algorithm[J]. Chinese Journal of Computers, 2003, 26(8): 974～981
[7] Yu J, Cheng Qs. A Note on The Weighting Exponent of FCM Algorithm[J]. ActaElectronicaSinica, 2003, 31(3): 478～480
[8] Yu J, Cheng Qs, Huang Hk. Analysis of the Weighting Exponent in the FCM[J]. Transactions onSystems, 2004, 34(1): 634～639
[9] Yu J. General C-Means Clustering Model and its Applications[A]. Proceedings of the 2003 IEEE Computer Society Conference on CVPR[C]. Madison, 2003. 122～127
[10] Robert W, Tian Sf. An Efficient Optimality Test of the Fuzzy C-Means Algorithm[A]. Proceedings of the 2002 IEEE International Conference[C]. Honolulu, 2002. 98～103
[11] Shi Hb. Counter Examples to Convergence Theorem of Maximum Entropy Clustering Algorithm[J]. Science in China, 2003, 46(5): 321～326
[12] Yuan B, Klir G J, Swan-Stone J F. Evolutionary Fuzzy C-Means Clustering Algorithm[J]. IEEE Trans on Control System Magazine, 1995, 36(9): 221～2226
[13] T M Mitchell. Machine Learning[M]. New York: McGraw-hill Companies INC, 1997. 67～94
[14] 斯塔夫·勒庞．乌合之众[M]．北京：中央编译出版社，1999
[15] Kimbedy C. Gleason, Ike Mathur , Mark A. Peterson . Analysis of Intraday Herding Behavior Among The Sector Effs[J]. Journal of Empirical Finance, 2004, 11: 681～694
[16] Calvo G., Mendoza E. Rational Herd Behavior and Globalization of Securities Markets[J]. Journal of International Economics, 2000, 51: 79～113
[17] Janis I. L. Victims ofGroupthink: A Psychological Study of Foreign-Policy Decision and Fiascoes[M]. Boston: Houghton Mifflin, 1972. 93～127
[18] Janis I. L., Mann L. Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment[M]. NewYork: Free Press, 1977
[19] Janis I. L. Groupthink: Psychological Studies of Policy Decisions and Fiascoes[M]. Boston: Houghton Mifflin, 1982
[20] 毕鹏程，席酉民．群体决策过程中的群体思维研究[J]．管理科学学报，2002，5(1)：25～34
[21] 毕鹏程，席酉民，王益谊．群体思维理论的发展及其实证研究综述[J]．管理科学学报，2004，7(4)：75～84
[22] Esser J. K. Alive and Well After 25 Years: A Review of Groupthink Research[J]. Organizational Behavior & Human Decision Processes, 1998, 73(2): 116～141
[23] 李武，席酉民，成思危．群体决策过程组织研究述评[J]．管理科学学报，2002，5(2)：55～66
[24] Agrawal A., Gibson C. C. Group Size and Collective Action: Third Party Monitoring in Common-Pool Resources[J]. Comparative Political Studies, 2001, 34(1): 63～93
[25] Bikhchandani. S, Hirshleifer. D, Welch. I, V. O. A Theory of Fad, Fashion, Custom, and Cultural Change as Informational Cascades[J]. Journal of Political Economy, 1992, 100(5): 992～1026
[26] Bikhcandani S., David H, Welch I. V. O. Learning From the Behavior of Others, Conformity, Fads, and InformationalCaseades[J]. Journal of Economic Perspectives, 1998, 12(3): 151～170
[27] Faure G O. Social Emotional Aspects of Negotiation[J]. European Journal of Operational Research, 1990, 46(2): 177～180
[28]] Clazer R, Stechel I H, Gafni A. Locally Rational Decision Making, The Distracting Effects of Information on Managerial Performance[J]. Management Science, 1992, 18(2): 212～227
[29] Goldstein W M, Einhorn H J. Expression Theory and the Preference Reversal Phenomena[J]. Psychological Review, 1987, 94 (2): 236～254
[30] Tversky A, Simonson I. Context-dependent Preferences[J]. Management Science, 1993, 39(10): 1179～1189
[31] Hai Zhuge. Conflict Decision Training Through Multi-Space Co-Operation[J]. Decision SupportSystems, 2000, 29:111～123
[32] J. Rose, D. A. Hensher. Modeling Agent Interdependency in Group Decision Making[J]. Transportation ResearchPart E, 2004, 40:63～79
[33] Jarzabkowski P., Rosalind H. S. Harnessing Diversity and Collective Action in the Top Management Team[J]. Long Range Planning, 2004, 37(2): 399～419
[34] Vogel B. Linking For Change: Network Action as Collective, Focused and Energetic Behavior[J]. Long Range Planning, 2005, 38(3): 531～553
[35] Pavlovich K. All That Jazz[J]. Long Range Planning, 2003, 36(5): 441～558
[36] Dick R. M., Digregorio M., McCarthy N. Methods for Studying Collective Action in Rural Development[J]. Agricultural Systems, 2004, 82(1): 197～214
[37] Bardhan P. Analytics of the Institutions of Informal Cooperation in Rural Development[J]. World Development, 1993, 21(4): 633～639
[38] Bardhan P. Irrigation and Cooperation: An Empirical Analysis of 48 Irrigation Communities in South India[J]. Economic Development and Cultural Change, 2000, 48(4): 847～865
[39]] Poteete A. R. Ostrom E. In Pursuit of Comparable Conceptions and Data about Collective Action[J]. Agricultural Systems, 2004, 82(1): 215～232
[40] Varughese. G. The Contested Role of Heterogeneity in Collective Action: Some Evidence From Community Forestry in Nepal[J]. World Development, 2001, 63 (3): 747～765
[41] 何贵兵，曾建华．分布式群体在动态系统控制决策中的内隐学习[J]．心理学报，2003，35(6)：777～786
[42] 李钊，刘新福，顾君忠．电子商务中群体决策行为的研究[J]．计算机工程，2002，28(9)：24～26
[43] 田军，张朋柱，王刊良，汪应洛．基于德尔菲法的专家意见集成模型研究[J]．系统工程理论与实践，2004，1：68～74
[44] 顾基发．意见综合—怎样达成共识[J]．系统工程学报，2001，16(5)：39～43
[45] 徐选华．网络环境下模型驱动的复杂大群体决策支持系统研究[博士学位论文]．长沙：中南大学，2005
[46] Andrews S.S, Lohr L, Cabrera M.L. A Bioeconomic Decision Model Comparing Composted and Fresh Litter for Winter Squash[J]. Agricultural Systems, 1999, 61 (3): 165～178
[47] Benbunan-Fich, Raque, Hiltz Starr Roxanne, Turoff Murray. A Comparative Content Analysis of Face-to-Face vs. Asynchronous Group Decision making[J]. Decision Support Systems, 2003, 34 (4): 457～469
[48] Silver, Steven D. A Dual-Motive Heuristic for Member Information Initiation in Group Decision Making: Managing Risk and Commitment[J]. Decision Support Systems, 1995, 15 (1): 83～97
[49] Van De Ven, et al,. Nominal Versus Interacting Group Process for Committee Making[J]. Academy of Management Journal, 1971, 14 (5): 129～139
[50] Jackie Rees, Gary J. Koehler. An Evolutionary Approach to Group Decision Making[J]. Journal on Computing, 2002, 14 (13): 278～292
[51] MacKay, David B, Bowen William M, Zinnes, Joseph L.A. Thurston Ian View of the Analytic Hierarchy Process[J]. European Journal of Operational Research, 1996, 89 (2): 427～444
[52] Hastak, Makarand. Advanced Automation or Conventional Construction Process[J]. Automation InConstruction, 1998, 7 (4): 299～314
[53] Bolloju N. Aggregation of Analytic Hierarchy Process Models Based on Similarities in Decision Makers' Preferences[J]. European Journal of Operational Research, 2001, 128 (3): 499～508
[54] 喻红阳．网络组织集成及其机制研究[博士学位论文]．武汉：武汉理工大学，2005
[55] Zhongsheng Hua, Feihua Huang. A Variable-Group Based Genetic Algorithm for Large-Scale Integer Programming[J]. Information Sciences, 2005, 8: 1～17
[56] Jackie Rees. Evolution in Groups: A Genetic Algorithm Approach to Group Decision Support System[J]. Information Technology and Management, 2003, 3: 213～227
[57] F. Herrera, L. Martinez. A 2-tuple Fuzzy Linguistic Representation Model for Computing with Words[J]. IEEE Transactions on Fuzzy Systems, 2000, 7 (4): 746～752
[58] Xu Zeshui. An Approach Based on the Uncertain Lowg and Induced Uncertain Lowg Operators to Group Decision Making with Uncertain Multiplicative Linguistic Preference Relations[J]. Decision Support Systems, 2004, 41 (2): 488～499
[59] 张道武，汤书昆，方兆本．进化的群体决策机制—联盟群决策方案德尔菲法一致性调整[J]．预测，2004，23(3)：36～40
[60] Zeeny M. Multiple Criteria Decision Making[J]. New York: McGraw-Hill, 1982
[61] Hwang C L, Lin M J. Group Decision Making under Multiple Criteria: Methods and Applications[J]. Berlin: Springer Press, 1987
[62] 陈延．决策分析[M]．北京：科学出版社，1987
[63] Chen S J. Hwang C L. Fuzzy Multiple Attribute Decision Making[M]. Berlin: Springer Press, 1992
[64] 陈南荣，仲伟俊．科学决策理论与方法[M]．南京：东南大学出版社，1996
[65] 席酉民，王应洛，陶谦坎．决策指标的估价方法及权的探讨[J]．系统工程与电子技术，1986，6(3)：12～16
[66] 唐克．目标的熵权模糊决策[J]．系统工程理论与实践，1992，12(4)：68～73
[67] 王宗军．多目标权系数赋值方法及其选择策略[J]．系统工程与电子技术，1993，15(6)：35～41
[68] 刘家学，刘耀武．带有方案偏好信息的多指标决策法[J]．系统工程与电子技术，1999，21(1)：4～7
[69] Solymosi T, Dinbu J. A Method for Determining the Weights of Criteria: the Centralized Weights[J]. European Journal of Operational Research, 1986, 26: 35～41
[70] Olson D L, Dorai V K. Implementation of the Centric Method of Scoliosis and Dumb[J]. European Journal of Operational Research, 1992, 60: 117～129
[71] Edwards W, Barron F H. Smarts and Smarter: Improved Simple Methods for Multi-attribute Utility Measurement[J]. Organizational Behavior and Human Decision Processed, 1994, 60:252～266
[72] Payphone M. On the Convergence of Multi-Attribute Weighting Methods[J]. European Journal of Operational Researeh, 2001, 129:569～585
[73] 王应明．应用离差最大化方法进行多指标决策与排序[J]．系统工程与电子技术，1998，20(7)：24～26
[74] 徐泽水，孙在东．一类不确定型多属性决策问题的排序方法[J]．管理科学学报，2002，5(3)：35～39
[75] Bryson N, Mobilizing A. An Action Learning Evaluation Procedure for Multiple Criteria Decision Making Problems[J]. European Journal of Operational Research, 1996, 96(2): 379～386
[76] 徐泽水．模糊综合评价的排序方法研究[M]．System Engineering Systems Science and Complexity Research．United Kingdom：Research Information Ltd出版社，2000．507～511
[77] 樊治平，张权．一种不确定性多属性决策模型的改进[J]．系统工程理论与实践，1999，19(12)：42～47
[78] 徐泽水．不完全信息下多目标决策的一种新方法[J]．运筹与管理，2001，10(2)：25～28
[79] 樊治平，胡国奋．区间数多属性决策的一种目标规划方法[J]．管理工程学报，2000，14(4)：50～52
[80] 徐泽水，张文献．多属性决策中的目标规划[J]．应用数学与计算数学学报，2001，15(2)：53～57
[81] 孙在东，徐泽水，达庆利．基于方案贴近度的不确定型多属性决策模型[J]．中国管理科学，2001，9(6)：58～62
[82] 徐泽水．部分权重信息下多目标决策方法研究[J]．系统工程理论与实践，2002，22(1)：43～47
[83] 王应明，张军奎．基于标准差和平均差的权系数确定方法及其应用[J]．数理统计与管理，2003，22(3)：22～26
[84] 黄定轩，武振业，宗蕴璋．基于属性重要性的多属性客观权重分配方法[J]．系统工程理论方法用，2004，13(3)：203～207
[85] 管红波，田大钢．基于属性重要性的决策树规则提取算法[J]．系统工程与电子技术，2004，26(3)：334～337
[86] Luce R D , Suppers P . Preferences, Utility and Subject Probability[J]. Handbook of Mathematical Psychology, 1965, 96(2): 249～410
[87] Tenino T. On Group Decision-Making Under Fuzzy Preferences[J]. Militiaperson Decision Making Using Fuzzy Sets and Possibility Theory, 1990, 9(3): 72～185
[88] 王宗军．集中式多目标权系数赋值方法[J]．系统工程理论与实践，1996，16(8)：12～19
[89] Chicano F. Integrating Three Representation Models in Fuzzy Multipurpose Decision Making Based on Fuzzy Preference Relations[J]. Fuzzy Sets and Systems, 1998, 97:33～48
[90] Chicano F. Integrating Multiplicative Preference Relations in a Multipurpose Decision Making Model Based on Fuzzy Preference Relations[J]. Fuzzy Sets and Systems, 2001, 122:277～291
[91] Herrera F. Militiaperson Decision-Making Based on Multiplicative Preference Relations[J]. European Journal of Operational Research, 2001, 129: 372～385
[92] Satyr T L. The Analytic Hierarchy Process[M]. New York: McGraw-Hill, 1980
[93] 李炎，范植华，洪志国，王勇．基于改进模糊聚类算法的评估数据一致性分析[J]．微型机与应用，2004，10(5)：56～58
[94] 王应明，傅国伟．关于专家最优评价模型的改进和完善[J]．系统工程，1992，10(6)：51～57
[95] 魏巍贤，冯佳．多目标权系数的组合赋权方法研究[J]．系统工程与电子技术，1998，20(2)：14～16
[96] 樊治平，张平，马建．多属性决策中权重确定的一种集成方法[J]．管理科学学报，1998，1(3)：50～53
[97] 陈华友．多属性决策中基于离差最大化的组合赋权方法[J]．系统工程与电子技术，2004，26(2)：194～197
[98] 郭春香，郭耀煌．基于偏序偏好的多属性群决策问题的综合权重[J]．系统工程与电子技术，2005，27(7)：1243～1246
[99] 樊治平，尤天慧，张全．多属性决策中基于加权模型的属性值灵敏度分析[J]．东北大学学报自然科学版，2002，23(1)：83～86
[100] 尤天慧，樊治平．不确定性多属性决策中确定熵权的一种误差分析方法[J]．系统工程，2003，21(1)：101～104
[101] 吴江，黄登仕．多属性决策中区间数偏好信息的一致化方法[J]．系统 工程理论方法应用，2003，12(4)：359～362
[102] Zadeh, L. A.. Fuzzy Sets[J]. Infonnation and Control, 1965, 8:338～353
[103] Liaag, G. S.. Fuzzy MCDM Based on Ideal and Anti-ideal Concepts[J]. European Journal of Operational Research, 1999, 112:682～691
[104] Chen, S. M.. ANew Method for Handling Multicriteria Fuzzy Decision Making Problems[J]. Cybernetics and Systems, 1994, 25:409～420
[105] Chang, P. L., Chen, Y. C.. A Fuzzy Multi-Criteria Decision Making Method for Technology Transfer Strategy Selection in Biotechnology[J]. Fuzzy Sets and Systems, 1994, 63:131～139
[106] R. C. Van Den Hornet. Decisional Powerin Group Decision Making: a Note on the Allocation of Group Member'S Weights in the Multiplicative AHP and Smart[J]. Group Decision and Negotiation, 2001, 10:275～286
[107] 王丹力，戴汝为．专家群体思维收敛的研究[J]．管理科学学报，2002，5(2)：1～5
[108] 元继学，吴祈宗．多属性群决策算法及一致性分析研究[J]．数学的实践与认识，2004，34(8)：51～57
[109] 江文奇，华中生．一种决策者判断一致性的聚类方法[J]．中国管理科学，2005，13(2)：35～39
[110] 安利平，陈增强，袁著祉．基于粗糙集理论的多属性决策分析[J]．控制与决策，2005，20(3)：294～298
[111] 徐泽水．基于残缺互补判断矩阵的交互式群决策方法[J]．控制与决策，2005，20(8)：913～916
[112] 姜艳萍，樊治平，王欣荣．AHP中判断矩阵一致性改进方法的研究[J]．东北大学学报(自然科学版)，2001，22(4)：468～470
[113] 陈侠，樊治平．基于互补判断矩阵的专家群体判断一致性分析[J]．东北大学学报(自然科学版)，2005，25(6)：595～598
[114] 宋海洲．群组决策的综合判断矩阵及一致性调整[J]．数学的实践与认识，2004，34(6)：52～59
[115] 翟晓燕，张新政．群组决策中判断的一致性协调与方案排序[J]．系统工程，2004，22(12)：96～100
[116] 沈建飞等．多指标方案评价中群体一致性的判断和调整方法[J]．工业工程与管理，2005，5：79～87
[117] His-Mei Hsu, Chen-Tung Chen. Aggregation of Fuzzy Opinions under Group Decision Making[J]. Fuzzy Sets and Systems, 1996, 79:279～285
[118] J. Kacprzzy, M. Fedrizzi, H. Nurmi. Group Decision Making and Preference and Fuzzy Majority[J]. Fuzzy Sets and Systems, 1992, 49:21～31
[119] 丁斌．动态Fuzzy图最大树聚类分析[J]．数值计算和计算机应用，1992，2：157～159
[120] Dae-Young Choi, Kyung-Whan Oh. ASA and its Application to Mufti-criteria Decision Making[J]. Fuzry Sets and Systems, 2000, 114:89～102
[121] A. I. C Olc er *, A. Y. Odabasi. ANew Fuzzy Multiple Attributive Group Decision Making Methodology and its Applicationto Propulsion/Maneuvering System Selection Problem[J]. European Journal of Operational Research, 2005, 166: 93～114
[122] Deng-Feng Li, Jian-Bo Yang. Fuzzy Linear Programming Technique for Multiattribute Group Decision Making in Fuzzy Environments[J]. Information Sciences, 2004, 158:263～275
[123] Hsuan-Shih Lee. Optimal Consensus of Fuzzy Opinions under Group Decision Making Environment[J]. Fuzzy Sets and Systems, 2002, 132:303～315
[124] Zhi-Ping Fan, Jian Ma b, Yan-Ping Jiang, Yong-Hong Sun a, Louis Ma. A Goal Programming Approach to Group Decision Making Based on Multiplicative Preference Relations and Fuzzy Preference Relations[J]. European Journal of Operational Research, 2005, 78 (4): 1～11
[125] Huey-Ming Lee. Group Decision Making Using Fuzzy Sets Theory for Evaluating the Rate of Aggregative Risk in Software Development[J]. Fuzzy Sets and Systems, 1996, 80:261～271
[126] 程启月，邱菀华，李建云．不确定性动态军事指挥决策的模糊熵分析[J]．系统工程理论方法应用，2002，11(13)：231～239
[127] 吕翔吴，李登峰．基于模糊信息的群体多维偏好分析决策模型[J]．系统工程与电子技术，2004，26(5)：605～607
[128] 陈守煜，王建明，伏广涛．决策信息不完全确知的模糊决策集成模型[J]．控制与决策，2002，17(6)：847～851
[129] 王建明，童幼堂，李登峰，汪德虎．群决策监督模糊模式识别模型[J]．控制与决策，2002，17(增)：672～675
[130] 元继学，吴祈宗，于向军．基于Bonissone近似算法的群决策方法[J]．数 学的实践与认识，2003，33(12)：66～71
[131] 樊治平，姜艳萍，肖四汉．基于OIYA算子的不同形式偏好信息的群决策方法[J]．控制与决策，2001，16(增)：749～752
[132] 周珍，吴祈宗，刘福祥．三角模糊数互补判断矩阵的一种排序方法及其在项目投资决策中的应用[J]．数学的实践与认识，2005，35(11)：74～77
[133] 徐玖平．基于Hausdorff度量模糊多指标群决策的TOPSIS方法[J]．系统工程理论与实践，2002，10：84～93
[134] 吕大刚，王力，张鹏，光远．模糊多属性决策的相似接近度解法[J]．控制与决策，2004，19(11)：1282～1285
[135] 兰继斌，徐扬，刘家忠．模糊多属性决策的折衷方法[J]．系统工程与电子技术，2004，26(1)：40～43
[136] 李荣钧．模糊决策的基础：模糊集比较与排序[J]．控制与决策，2003，18(2)：221～224
[137] 何亚群，胡寿松．一种基于粗糙模糊集成模型的决策分析方法[J]．控制与决策，2004，19(3)：315～318
[138] 彭怡，胡杨，郭耀煌．基于群体理想解的多属性群决策算法[J]．西南交通大学学报，2003，38(6)：682～685
[139] 夏勇其，吴祈宗．一种混合型多属性决策问题的TOPSIS方法[J]．系统工程学报，2004，19(6)：630～634
[140] 于春海，樊治平．一种基于群体语言相似矩阵的聚类方法[J]．系统工程，2004，22(7)：76～79
[141] 徐章艳，尹云飞．一种区间值聚类的数据挖掘方法[J]．系统工程与电子技术，2005，27(3)：565～567
[142] 江文奇，华中生．一种改进的群体效用集结方法[J]．系统工程与电子技术，2005，27(2)：253～256
[143] J. Claussen, A. Kemper, D. Kossmann, C. Wiesner. Exploiting Early Sorting and Early Partitioning for Decision Support Query Processing[J]. The VLDB Journal, 2000, 9:190～213
[144] Soung Hie Kim, Sang Hyun Choi, Jae Kyeong Kim. An Interactive Procedure for Multiple Attribute Group Decision Making With Incomplete Information: Range-based Approach[J]. European Journal of Operational Research, 1999, 118: 139～152
[145] Takehiro Inohara. Cluster Ability of Groups and Information Exchange in Group Decision Making with Approval Voting System[J]. Applied Mathematics and Computation, 2003, 136: 1～15
[146] Fo Herrera, E. Herrera-Viedma, J. L. Verdegay. AModel of Consensus in Group Decision Making under Linguistic Assessments[J]. Fuzzy Sets and Systems, 1996, 78: 73～87
[147] Sajjad Zahir. Clusters in a Group: Decision Making in the Vector Space Formulation of the Analytic Hierarchy Process[J]. European Journal of Operational, 1999, 112:620～634
[148] Chen Xiaohong, Lai Bangchuan, Luo Ding. Mining Association Rule Eff iciently Based on Data Warehouse[J]. Cent. South univ. Technol, 2003, 10: 375～380
[149] 高峰记，黄咏芳，任晓燕．多指标区间决策的理想点贴近法[J]．数学的实践与认识，2005，35(1)：30～33
[150] 徐泽水，达庆利．区间型多属性决策的一种新方法[J]．东南大学学报自然科学版，2003，33(4)：498～501
[151] 王爱玲．群决策方法研究[J]．统计与决策，2002，4：29～31
[152] 樊治平，李洪燕，姜艳萍．基于OWA算子的群决策方法的灵敏度分析[J]．东北大学学报自然科学版，2004，25(11)：1114～1117
[153] 王坚强．一种新的有优序综合评价的群决策方法[J]．系统工程与电子技术，2002，24(8)：21～23
[154] 宋光兴，邹平．多属性决策的群排序方法研究[J]．运筹与管理，2002，11(3)：27～31
[155] 徐泽水．基于方案达成度和综合度的交互式多属性决策法[J]．控制与决策，2002，17(4)：435～438
[156]姜灵敏，陈松乔．一种基于模糊聚类分析的综合排序算法[J]．计算机工程与应用，2003，36：90～92
[157] 曹荣增，李一军．一种基于偏好分布的群决策方法[J]．管理工程学报，2004，18(3)：121～124
[158] Gungor, Z., Arikan, F. A Fuzzy Outranking Method in Energy Policy Planning[J]. Fuzzy Sets and Systems, 2000, 58 (4): 114～122
[159] Ljubisa vlacic, Michio amagasa. Applying Multi-Attribute-bases Group Decision Making Techniques in Complex Equipment Selection Tasks[J]. Group Decision and Negotiation, 1997, 6: 529～556
[160] 陈建军，杨振山．基于智能体和数据仓库的群决策支持系统[J]．微机发展，2004，14(1)：1～3
[161] Korhonen. P., Moskowitz. H., Wallenius. J.. Multiple Criteria Decision Support: A Review[J]. European Journal of Opemtional Research, 1992, 63: 361～375
[162] T．X．Bui著，席酉民，侯宁霞译．群体决策支持系统[M]．西安：西安交通大学出版社，1992
[163] 卓越等．群决策支持系统中的一致性分析技术[J]．控制与决策，1999，14(6)：636～641
[164] 俞伟，陈学广．群件对群决策支持系统性能影响的研究[J]．兵工自动化，2003，22(1)：1～3
[165] 李必强，胡浩．系统集成数据仓库与模糊群决策理论的决策支持系统[J]．武汉理工大学学报信息与管理工程版，2004，26(6)：21～23
[166] 徐选华，陈晓红．基于Multi-Agent的决策支持系统模型管理研究[J]．计算机工程与应用，2005，13：194～196
[167] 徐选华，陈晓红．群体决策支持系统的模型库研究[J]．中南大学学报社会科学版，2003，9(4)：505～507
[168] 陈晓红，周艳菊．基于遗传算法的群体决策支持系统有效性的评价[J]．系统工程，2001，19(6)：55～58
[169] 陶庆，王威．决策支持系统的模糊综合评价[J]．数学的实践与认识，2005，35(5)：71～79
[170] 陈晓红，周艳菊．基于层次模型法的互联网环境下的群体决策支持系统[J]．中国管理科学，2001，9(6)：49～57
[171] 翟丽丽．基于Internet的多属性评价群决策支持系统总体设计[J]．哈尔滨理工大学学报，2004，9(1)：69～71
[172] 张相斌，杨德礼．基于多属性的系统结构建模与分析方法[J]．系统工程理论方法应用，2002，11(2)：146～152
[173] Reay-Chen Wang, Shian-Jong Chuu. Group Decision-making Using a Fuzzy Linguistic Approach for Evaluating the Flexibility in a Manufacturing System[J]. European Journal of Operational Research, 2004, 154: 563～572
[174] Datta A, Thomas H. The Cube Data Model: a Conceptual Model and Algebra for On-line Analytical Processing in Data Warehouses[J]. Decision Support Systems, 1999, 27(3): 289～301
[175] Ruspini E H. A New Approach to Clustering[J]. Fuzzy sets and systems, 1969, 15(1): 22～32
[176] Tamra S, et al. Pattern Classification Based on Fuzzy Relations[J]. IEEE Trans SMC, 1971, 1(1): 217～242
[177] Backer E, Jain A K. A Clustering Performance Measure Based on Fuzzy Set Decomposition[J]. IEEE Trans PAMI, 1981, 3(1): 66～74
[178] Dunn J C. A Graph Theoretic Analysis of Pattern Classification via Tamura's Fuzzy Relation[J]. IEEE Trans SMC, 1974, 4(3): 310～313
[179] Matula D W. Graph Theoretic Techniques for Cluster Analysis Algorithms[A]. In: J Van Ryzin. Proceedings of the Advanced Seminar on Classification and Clustering[C]. New York: Academic Society, 1977. 95～129
[180] Bezdek J C, Harris J O. Convex Decompositions of Fuzzy Partitions[J]. IEEE Trans on JMAA, 1979, 67: 490～512
[181] Esogbue A O. Optimal Clustering of Fuzzy Data via Fuzzy Dynamic Programming[J]. FSS, 1986, 18: 283～298
[182] Mantaras R L D, Valverde L. New Results in Fuzzy Clustering Based on the Concept of Indistinguishably Relation[J]. IEEE Trans on PAMI, 1988, 10(5): 754～757
[183] Duda R O, Hart P E. Pattern Classification and Scene Analysis[J]. New York: John Wiley& Sons Press, 1973
[184] Dunn J C. Well-Separated Clusters and the Optimal Fuzzy Partitions[J]. Fuzzy Sets and Systems, 1974, 4(1): 95～104
[185] Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms[M]. New York: Plenum Press, 1981
[186] Bezdek J C. A Convergence Theorem for the Fuzzy Isodata Clustering Algorithm[J]. IEEE Trans on PAMI, 1980, 1(2): 1～8
[187] 赵恒，杨万海．基于属性加权的模糊K-Modes聚类算法[J]．系统工程与电子技术，2003，25(10)：1229～1302
[188] Bezdek JC. Clustering Validity with Fuzzy Sets[J]. Journal of mathematical biology, 1974, 22(1): 57～71
[189] 王连亮，陈怀新．基于改进的模糊C-均值的分级递减聚类算法[J]．系统工程与电子技术，2005，27(7)：1304～1306
[190] 孔锐，张国宣，施泽生，郭立．基于核的K-均值聚类[J]．计算机工程， 2004，30(11)：12～13
[191] 刘纪平，汪宏斌，汪诚波，周洞汝．基于模糊最近邻的高维数据聚类[J]．小型微型计算机系统，2005，26(2)：261～263
[192] 张曙红，孙建勋，诸克军．基于遗传优化的采样模糊C均值聚类算法[J]．系统工程理论与实践，2004，5：121～125
[193] 陈晓红，秦杨．基于映射簇的Web数据挖掘研究[J]．系统工程，2004，22(7)：80～83
[194] 沈红斌，王士同，吴小俊．离群模糊核聚类算法[J]．软件学报，2004，15(7)：1021～1029
[195] 张新波．两阶段模糊C-均值聚类算法[J]．电路与系统学报，2005，10(2)：117～120
[196] 李侃，刘玉树．模糊核聚类的自适应算法[J]．控制与决策，2004，19(5)：595～597
[197] Panayirc E. A Test for Multidimensional Clustering Tendency[J]. Pattern Recognition, 1983, 16(4): 434～444
[198] 诸克军，苏顺华，黎金玲．模糊C-均值中的最优聚类与最佳聚类数[J]．系统工程理论与实践，2005，3：52～61
[199] 于春海，樊治平．一种基于区间数多指标信息的FCM聚类算法[J]．系统工程学报，2004，19(4)：387～393
[200] 李洁，高新波，焦李成．一种基于修正划分模糊度的聚类有效性函数[J]．系统工程与电子技术，2005，27(4)：723～726
[201] 王元珍，王健，李晨阳．一种改进的模糊聚类算法[J]．华中科技大学学报(自然科学版)，2005，33(2)：92～94
[202] 陈晓红，刘蓉．改进的聚类算法及在复杂大群体决策中的应用[J]．系统工程与电子技术(已录用)
[203] Liu Rong, Chen Xiaohong. Continuous Trust Building Methods Basing on Cluster-Head in VE[A]. Proceedings of the 5rdWuhan International Conference on E-Business[C]. Wuhan, China, 2006
[204] 刘蓉．数据挖掘及其在通信企业经营分析领域的应用[J]．科技进步与对策，2004，10：159～161
[205] 蒋长浩．图论与网络流[M]．北京：中国林业出版社，2001．21～35，98～119
[206] M. L. Garey, D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness[M]. San Francisco: W. H. Freeman, 1979
[207] Sudipto Guha, Samir Khuller. Approximation Algorithms for Connected Dominating Sets[A]. Proceedings of the 4rdAnnual European Symposium on Algorithms[C]. Barcelona: The Fourth Annual European Symposium, 1996
[208] Mullen B, Anthony T, Salas E. Group Cohesiveness and Quality of Decision Making: An Integration of Tests of the Group Think Hypotheses[J]. Small Group Research, 1994, (25): 189～204
[209] Kevin Tasa, Glen Whyte. Collective Efficacy and Vigilant Problem Solving in Group Decision Making: A Non-Linear Model[J]. Organizational Behavior and Human Decision Processes, 2005, (96): 119～129
[210] ELIZABETH M. JAKOB. Individual Decisions and Group Dynamics: Why Policed Spiders Join and Leave Groups[J]. Animal behavior, 2004, (68): 9～20
[211] Wheelan S, Hochberger J. Validation Studies of the Group Development Questionnaire[J]. Small Group Research, 1996, 27(1): 143～170
[212] 毕鹏程，席酉民，王益谊．群体发展过程中的群体思维演变研究[J]．预测，2005，24(3)：1～7
[213] Wheelan S. Facilitating Training Groups: A Guide to Leadership and Verbal Intervention Skills[J]. Small Group Research, 1990
[214] Wheelan S. Group Processes: A Developmental Perspective[M]. Boston: Ally & Bacon, 1994
[215] Michael R., Baumann, Bryan L. Bonner. The Effects of Variability and Expectations on Utilization of Member Expertise and Group Performance[J]. Organizational Behavior and Human Decision Processes, 2004, 93: 89～101
[216] 柯年满，王重鸣．多层次团队决策理论及其进展[J]．心理科学，2003，26(3)：527～528
[217] 毕鹏程，郎淳刚，席酉民．领导风格和行为对群体决策过程和结果的影响[J]．西安交通大学学报(社会科学版)，2005，25(2)：1～10
[218] William Schiano, Joseph W. Weiss. Y2K All Over Again: How Groupthink Permeates and Compromises Security[J]. Business Horizons, 2006, 49: 115～125
[219] Sarwar B, Karypis G, Konstan J et al. Item-based Collaborative Filtering Recommendation Algorithms[A]. Proceedings of the 10rdinternational World Wide Web Conference[C]. Houston, 2001. 285～295
[220] 邓爱林，朱扬勇，施伯乐等．基于项目评分预测的协同过滤推荐算法[J]．软件学报，2003，14(9)：1621～1628
[221] 徐仲．矩阵论简明教程[M]．北京：科学出版社，2002
[222] 侯如成，陈守煜．水库防洪调度多目标模糊群决策方法[J]．水利学报，2004，12．106～111
[223] 王熙照，王亚东等．学习特征权值对K-均值聚类算法的优化[J]．计算机研究与发展，2003，40(6)：869～873
[224] D S Yeung, E C C Tsang. Weighted Fuzzy Production Rules[J]. Fuzzy Sets and Systems, 1997, 88: 299～313
[225] J Basak, R K De, S K Pal. Unsupervised Feature Selection Using A Neuron-Fuzzy Approach[J]. Pattern Recognition Letters, 1998, 19(11): 997～1006
[226] 倪国熙．常用的矩阵理论和方法[M]．上海：上海科学技术出版社，1984．176
[227] Reimnt B, Robert G. Supporting Group Decision Process With Software Agents[A]. Proceedings of the 3rdIS-DSS Conference[C]. Hong Kong, 1995.
[228]David Hand等．Printiples of Data Mining(数据挖掘原理)[M]．北京：机械工业出版社，2003
[229] 周磊．中国在线消费者对在线营销者信任问题的实证研究[博士学位论文]．上海：复旦大学，2005
[230] Fishbein, M and Ajzen I. Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research[J]. Addison-Wesley, Reading, 1975, 12: 36～39
[2] 高新波．模糊聚类分析及其应用[M]．西安：西安电子科技大学出版社，2004．39～69
[3] Zadeh L A. Fuzzy Logic[J]. IEEE Trans on Control System Magazine, 1988, 11(15): 83～93
[4] 朱剑英．应用模糊数学方法的若干问题及处理方法[J]．模糊系统与数学，1992，11(2)：57～63
[5] Yu J , Huang Hk A New Weighting Fuzzy C-Means Algorithms[A]. Proceedings of the 12th IEEE Conf on Fuzzy Systems[C]. Louis, 2003. 896～901
[6] Yu J. On the Fuzziness Index of the FCM Algorithm[J]. Chinese Journal of Computers, 2003, 26(8): 974～981
[7] Yu J, Cheng Qs. A Note on The Weighting Exponent of FCM Algorithm[J]. ActaElectronicaSinica, 2003, 31(3): 478～480
[8] Yu J, Cheng Qs, Huang Hk. Analysis of the Weighting Exponent in the FCM[J]. Transactions onSystems, 2004, 34(1): 634～639
[9] Yu J. General C-Means Clustering Model and its Applications[A]. Proceedings of the 2003 IEEE Computer Society Conference on CVPR[C]. Madison, 2003. 122～127
[10] Robert W, Tian Sf. An Efficient Optimality Test of the Fuzzy C-Means Algorithm[A]. Proceedings of the 2002 IEEE International Conference[C]. Honolulu, 2002. 98～103
[11] Shi Hb. Counter Examples to Convergence Theorem of Maximum Entropy Clustering Algorithm[J]. Science in China, 2003, 46(5): 321～326
[12] Yuan B, Klir G J, Swan-Stone J F. Evolutionary Fuzzy C-Means Clustering Algorithm[J]. IEEE Trans on Control System Magazine, 1995, 36(9): 221～2226
[13] T M Mitchell. Machine Learning[M]. New York: McGraw-hill Companies INC, 1997. 67～94
[14] 斯塔夫·勒庞．乌合之众[M]．北京：中央编译出版社，1999
[15] Kimbedy C. Gleason, Ike Mathur , Mark A. Peterson . Analysis of Intraday Herding Behavior Among The Sector Effs[J]. Journal of Empirical Finance, 2004, 11: 681～694
[16] Calvo G., Mendoza E. Rational Herd Behavior and Globalization of Securities Markets[J]. Journal of International Economics, 2000, 51: 79～113
[17] Janis I. L. Victims ofGroupthink: A Psychological Study of Foreign-Policy Decision and Fiascoes[M]. Boston: Houghton Mifflin, 1972. 93～127
[18] Janis I. L., Mann L. Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment[M]. NewYork: Free Press, 1977
[19] Janis I. L. Groupthink: Psychological Studies of Policy Decisions and Fiascoes[M]. Boston: Houghton Mifflin, 1982
[20] 毕鹏程，席酉民．群体决策过程中的群体思维研究[J]．管理科学学报，2002，5(1)：25～34
[21] 毕鹏程，席酉民，王益谊．群体思维理论的发展及其实证研究综述[J]．管理科学学报，2004，7(4)：75～84
[22] Esser J. K. Alive and Well After 25 Years: A Review of Groupthink Research[J]. Organizational Behavior & Human Decision Processes, 1998, 73(2): 116～141
[23] 李武，席酉民，成思危．群体决策过程组织研究述评[J]．管理科学学报，2002，5(2)：55～66
[24] Agrawal A., Gibson C. C. Group Size and Collective Action: Third Party Monitoring in Common-Pool Resources[J]. Comparative Political Studies, 2001, 34(1): 63～93
[25] Bikhchandani. S, Hirshleifer. D, Welch. I, V. O. A Theory of Fad, Fashion, Custom, and Cultural Change as Informational Cascades[J]. Journal of Political Economy, 1992, 100(5): 992～1026
[26] Bikhcandani S., David H, Welch I. V. O. Learning From the Behavior of Others, Conformity, Fads, and InformationalCaseades[J]. Journal of Economic Perspectives, 1998, 12(3): 151～170
[27] Faure G O. Social Emotional Aspects of Negotiation[J]. European Journal of Operational Research, 1990, 46(2): 177～180
[28]] Clazer R, Stechel I H, Gafni A. Locally Rational Decision Making, The Distracting Effects of Information on Managerial Performance[J]. Management Science, 1992, 18(2): 212～227
[29] Goldstein W M, Einhorn H J. Expression Theory and the Preference Reversal Phenomena[J]. Psychological Review, 1987, 94 (2): 236～254
[30] Tversky A, Simonson I. Context-dependent Preferences[J]. Management Science, 1993, 39(10): 1179～1189
[31] Hai Zhuge. Conflict Decision Training Through Multi-Space Co-Operation[J]. Decision SupportSystems, 2000, 29:111～123
[32] J. Rose, D. A. Hensher. Modeling Agent Interdependency in Group Decision Making[J]. Transportation ResearchPart E, 2004, 40:63～79
[33] Jarzabkowski P., Rosalind H. S. Harnessing Diversity and Collective Action in the Top Management Team[J]. Long Range Planning, 2004, 37(2): 399～419
[34] Vogel B. Linking For Change: Network Action as Collective, Focused and Energetic Behavior[J]. Long Range Planning, 2005, 38(3): 531～553
[35] Pavlovich K. All That Jazz[J]. Long Range Planning, 2003, 36(5): 441～558
[36] Dick R. M., Digregorio M., McCarthy N. Methods for Studying Collective Action in Rural Development[J]. Agricultural Systems, 2004, 82(1): 197～214
[37] Bardhan P. Analytics of the Institutions of Informal Cooperation in Rural Development[J]. World Development, 1993, 21(4): 633～639
[38] Bardhan P. Irrigation and Cooperation: An Empirical Analysis of 48 Irrigation Communities in South India[J]. Economic Development and Cultural Change, 2000, 48(4): 847～865
[39]] Poteete A. R. Ostrom E. In Pursuit of Comparable Conceptions and Data about Collective Action[J]. Agricultural Systems, 2004, 82(1): 215～232
[40] Varughese. G. The Contested Role of Heterogeneity in Collective Action: Some Evidence From Community Forestry in Nepal[J]. World Development, 2001, 63 (3): 747～765
[41] 何贵兵，曾建华．分布式群体在动态系统控制决策中的内隐学习[J]．心理学报，2003，35(6)：777～786
[42] 李钊，刘新福，顾君忠．电子商务中群体决策行为的研究[J]．计算机工程，2002，28(9)：24～26
[43] 田军，张朋柱，王刊良，汪应洛．基于德尔菲法的专家意见集成模型研究[J]．系统工程理论与实践，2004，1：68～74
[44] 顾基发．意见综合—怎样达成共识[J]．系统工程学报，2001，16(5)：39～43
[45] 徐选华．网络环境下模型驱动的复杂大群体决策支持系统研究[博士学位论文]．长沙：中南大学，2005
[46] Andrews S.S, Lohr L, Cabrera M.L. A Bioeconomic Decision Model Comparing Composted and Fresh Litter for Winter Squash[J]. Agricultural Systems, 1999, 61 (3): 165～178
[47] Benbunan-Fich, Raque, Hiltz Starr Roxanne, Turoff Murray. A Comparative Content Analysis of Face-to-Face vs. Asynchronous Group Decision making[J]. Decision Support Systems, 2003, 34 (4): 457～469
[48] Silver, Steven D. A Dual-Motive Heuristic for Member Information Initiation in Group Decision Making: Managing Risk and Commitment[J]. Decision Support Systems, 1995, 15 (1): 83～97
[49] Van De Ven, et al,. Nominal Versus Interacting Group Process for Committee Making[J]. Academy of Management Journal, 1971, 14 (5): 129～139
[50] Jackie Rees, Gary J. Koehler. An Evolutionary Approach to Group Decision Making[J]. Journal on Computing, 2002, 14 (13): 278～292
[51] MacKay, David B, Bowen William M, Zinnes, Joseph L.A. Thurston Ian View of the Analytic Hierarchy Process[J]. European Journal of Operational Research, 1996, 89 (2): 427～444
[52] Hastak, Makarand. Advanced Automation or Conventional Construction Process[J]. Automation InConstruction, 1998, 7 (4): 299～314
[53] Bolloju N. Aggregation of Analytic Hierarchy Process Models Based on Similarities in Decision Makers' Preferences[J]. European Journal of Operational Research, 2001, 128 (3): 499～508
[54] 喻红阳．网络组织集成及其机制研究[博士学位论文]．武汉：武汉理工大学，2005
[55] Zhongsheng Hua, Feihua Huang. A Variable-Group Based Genetic Algorithm for Large-Scale Integer Programming[J]. Information Sciences, 2005, 8: 1～17
[56] Jackie Rees. Evolution in Groups: A Genetic Algorithm Approach to Group Decision Support System[J]. Information Technology and Management, 2003, 3: 213～227
[57] F. Herrera, L. Martinez. A 2-tuple Fuzzy Linguistic Representation Model for Computing with Words[J]. IEEE Transactions on Fuzzy Systems, 2000, 7 (4): 746～752
[58] Xu Zeshui. An Approach Based on the Uncertain Lowg and Induced Uncertain Lowg Operators to Group Decision Making with Uncertain Multiplicative Linguistic Preference Relations[J]. Decision Support Systems, 2004, 41 (2): 488～499
[59] 张道武，汤书昆，方兆本．进化的群体决策机制—联盟群决策方案德尔菲法一致性调整[J]．预测，2004，23(3)：36～40
[60] Zeeny M. Multiple Criteria Decision Making[J]. New York: McGraw-Hill, 1982
[61] Hwang C L, Lin M J. Group Decision Making under Multiple Criteria: Methods and Applications[J]. Berlin: Springer Press, 1987
[62] 陈延．决策分析[M]．北京：科学出版社，1987
[63] Chen S J. Hwang C L. Fuzzy Multiple Attribute Decision Making[M]. Berlin: Springer Press, 1992
[64] 陈南荣，仲伟俊．科学决策理论与方法[M]．南京：东南大学出版社，1996
[65] 席酉民，王应洛，陶谦坎．决策指标的估价方法及权的探讨[J]．系统工程与电子技术，1986，6(3)：12～16
[66] 唐克．目标的熵权模糊决策[J]．系统工程理论与实践，1992，12(4)：68～73
[67] 王宗军．多目标权系数赋值方法及其选择策略[J]．系统工程与电子技术，1993，15(6)：35～41
[68] 刘家学，刘耀武．带有方案偏好信息的多指标决策法[J]．系统工程与电子技术，1999，21(1)：4～7
[69] Solymosi T, Dinbu J. A Method for Determining the Weights of Criteria: the Centralized Weights[J]. European Journal of Operational Research, 1986, 26: 35～41
[70] Olson D L, Dorai V K. Implementation of the Centric Method of Scoliosis and Dumb[J]. European Journal of Operational Research, 1992, 60: 117～129
[71] Edwards W, Barron F H. Smarts and Smarter: Improved Simple Methods for Multi-attribute Utility Measurement[J]. Organizational Behavior and Human Decision Processed, 1994, 60:252～266
[72] Payphone M. On the Convergence of Multi-Attribute Weighting Methods[J]. European Journal of Operational Researeh, 2001, 129:569～585
[73] 王应明．应用离差最大化方法进行多指标决策与排序[J]．系统工程与电子技术，1998，20(7)：24～26
[74] 徐泽水，孙在东．一类不确定型多属性决策问题的排序方法[J]．管理科学学报，2002，5(3)：35～39
[75] Bryson N, Mobilizing A. An Action Learning Evaluation Procedure for Multiple Criteria Decision Making Problems[J]. European Journal of Operational Research, 1996, 96(2): 379～386
[76] 徐泽水．模糊综合评价的排序方法研究[M]．System Engineering Systems Science and Complexity Research．United Kingdom：Research Information Ltd出版社，2000．507～511
[77] 樊治平，张权．一种不确定性多属性决策模型的改进[J]．系统工程理论与实践，1999，19(12)：42～47
[78] 徐泽水．不完全信息下多目标决策的一种新方法[J]．运筹与管理，2001，10(2)：25～28
[79] 樊治平，胡国奋．区间数多属性决策的一种目标规划方法[J]．管理工程学报，2000，14(4)：50～52
[80] 徐泽水，张文献．多属性决策中的目标规划[J]．应用数学与计算数学学报，2001，15(2)：53～57
[81] 孙在东，徐泽水，达庆利．基于方案贴近度的不确定型多属性决策模型[J]．中国管理科学，2001，9(6)：58～62
[82] 徐泽水．部分权重信息下多目标决策方法研究[J]．系统工程理论与实践，2002，22(1)：43～47
[83] 王应明，张军奎．基于标准差和平均差的权系数确定方法及其应用[J]．数理统计与管理，2003，22(3)：22～26
[84] 黄定轩，武振业，宗蕴璋．基于属性重要性的多属性客观权重分配方法[J]．系统工程理论方法用，2004，13(3)：203～207
[85] 管红波，田大钢．基于属性重要性的决策树规则提取算法[J]．系统工程与电子技术，2004，26(3)：334～337
[86] Luce R D , Suppers P . Preferences, Utility and Subject Probability[J]. Handbook of Mathematical Psychology, 1965, 96(2): 249～410
[87] Tenino T. On Group Decision-Making Under Fuzzy Preferences[J]. Militiaperson Decision Making Using Fuzzy Sets and Possibility Theory, 1990, 9(3): 72～185
[88] 王宗军．集中式多目标权系数赋值方法[J]．系统工程理论与实践，1996，16(8)：12～19
[89] Chicano F. Integrating Three Representation Models in Fuzzy Multipurpose Decision Making Based on Fuzzy Preference Relations[J]. Fuzzy Sets and Systems, 1998, 97:33～48
[90] Chicano F. Integrating Multiplicative Preference Relations in a Multipurpose Decision Making Model Based on Fuzzy Preference Relations[J]. Fuzzy Sets and Systems, 2001, 122:277～291
[91] Herrera F. Militiaperson Decision-Making Based on Multiplicative Preference Relations[J]. European Journal of Operational Research, 2001, 129: 372～385
[92] Satyr T L. The Analytic Hierarchy Process[M]. New York: McGraw-Hill, 1980
[93] 李炎，范植华，洪志国，王勇．基于改进模糊聚类算法的评估数据一致性分析[J]．微型机与应用，2004，10(5)：56～58
[94] 王应明，傅国伟．关于专家最优评价模型的改进和完善[J]．系统工程，1992，10(6)：51～57
[95] 魏巍贤，冯佳．多目标权系数的组合赋权方法研究[J]．系统工程与电子技术，1998，20(2)：14～16
[96] 樊治平，张平，马建．多属性决策中权重确定的一种集成方法[J]．管理科学学报，1998，1(3)：50～53
[97] 陈华友．多属性决策中基于离差最大化的组合赋权方法[J]．系统工程与电子技术，2004，26(2)：194～197
[98] 郭春香，郭耀煌．基于偏序偏好的多属性群决策问题的综合权重[J]．系统工程与电子技术，2005，27(7)：1243～1246
[99] 樊治平，尤天慧，张全．多属性决策中基于加权模型的属性值灵敏度分析[J]．东北大学学报自然科学版，2002，23(1)：83～86
[100] 尤天慧，樊治平．不确定性多属性决策中确定熵权的一种误差分析方法[J]．系统工程，2003，21(1)：101～104
[101] 吴江，黄登仕．多属性决策中区间数偏好信息的一致化方法[J]．系统 工程理论方法应用，2003，12(4)：359～362
[102] Zadeh, L. A.. Fuzzy Sets[J]. Infonnation and Control, 1965, 8:338～353
[103] Liaag, G. S.. Fuzzy MCDM Based on Ideal and Anti-ideal Concepts[J]. European Journal of Operational Research, 1999, 112:682～691
[104] Chen, S. M.. ANew Method for Handling Multicriteria Fuzzy Decision Making Problems[J]. Cybernetics and Systems, 1994, 25:409～420
[105] Chang, P. L., Chen, Y. C.. A Fuzzy Multi-Criteria Decision Making Method for Technology Transfer Strategy Selection in Biotechnology[J]. Fuzzy Sets and Systems, 1994, 63:131～139
[106] R. C. Van Den Hornet. Decisional Powerin Group Decision Making: a Note on the Allocation of Group Member'S Weights in the Multiplicative AHP and Smart[J]. Group Decision and Negotiation, 2001, 10:275～286
[107] 王丹力，戴汝为．专家群体思维收敛的研究[J]．管理科学学报，2002，5(2)：1～5
[108] 元继学，吴祈宗．多属性群决策算法及一致性分析研究[J]．数学的实践与认识，2004，34(8)：51～57
[109] 江文奇，华中生．一种决策者判断一致性的聚类方法[J]．中国管理科学，2005，13(2)：35～39
[110] 安利平，陈增强，袁著祉．基于粗糙集理论的多属性决策分析[J]．控制与决策，2005，20(3)：294～298
[111] 徐泽水．基于残缺互补判断矩阵的交互式群决策方法[J]．控制与决策，2005，20(8)：913～916
[112] 姜艳萍，樊治平，王欣荣．AHP中判断矩阵一致性改进方法的研究[J]．东北大学学报(自然科学版)，2001，22(4)：468～470
[113] 陈侠，樊治平．基于互补判断矩阵的专家群体判断一致性分析[J]．东北大学学报(自然科学版)，2005，25(6)：595～598
[114] 宋海洲．群组决策的综合判断矩阵及一致性调整[J]．数学的实践与认识，2004，34(6)：52～59
[115] 翟晓燕，张新政．群组决策中判断的一致性协调与方案排序[J]．系统工程，2004，22(12)：96～100
[116] 沈建飞等．多指标方案评价中群体一致性的判断和调整方法[J]．工业工程与管理，2005，5：79～87
[117] His-Mei Hsu, Chen-Tung Chen. Aggregation of Fuzzy Opinions under Group Decision Making[J]. Fuzzy Sets and Systems, 1996, 79:279～285
[118] J. Kacprzzy, M. Fedrizzi, H. Nurmi. Group Decision Making and Preference and Fuzzy Majority[J]. Fuzzy Sets and Systems, 1992, 49:21～31
[119] 丁斌．动态Fuzzy图最大树聚类分析[J]．数值计算和计算机应用，1992，2：157～159
[120] Dae-Young Choi, Kyung-Whan Oh. ASA and its Application to Mufti-criteria Decision Making[J]. Fuzry Sets and Systems, 2000, 114:89～102
[121] A. I. C Olc er *, A. Y. Odabasi. ANew Fuzzy Multiple Attributive Group Decision Making Methodology and its Applicationto Propulsion/Maneuvering System Selection Problem[J]. European Journal of Operational Research, 2005, 166: 93～114
[122] Deng-Feng Li, Jian-Bo Yang. Fuzzy Linear Programming Technique for Multiattribute Group Decision Making in Fuzzy Environments[J]. Information Sciences, 2004, 158:263～275
[123] Hsuan-Shih Lee. Optimal Consensus of Fuzzy Opinions under Group Decision Making Environment[J]. Fuzzy Sets and Systems, 2002, 132:303～315
[124] Zhi-Ping Fan, Jian Ma b, Yan-Ping Jiang, Yong-Hong Sun a, Louis Ma. A Goal Programming Approach to Group Decision Making Based on Multiplicative Preference Relations and Fuzzy Preference Relations[J]. European Journal of Operational Research, 2005, 78 (4): 1～11
[125] Huey-Ming Lee. Group Decision Making Using Fuzzy Sets Theory for Evaluating the Rate of Aggregative Risk in Software Development[J]. Fuzzy Sets and Systems, 1996, 80:261～271
[126] 程启月，邱菀华，李建云．不确定性动态军事指挥决策的模糊熵分析[J]．系统工程理论方法应用，2002，11(13)：231～239
[127] 吕翔吴，李登峰．基于模糊信息的群体多维偏好分析决策模型[J]．系统工程与电子技术，2004，26(5)：605～607
[128] 陈守煜，王建明，伏广涛．决策信息不完全确知的模糊决策集成模型[J]．控制与决策，2002，17(6)：847～851
[129] 王建明，童幼堂，李登峰，汪德虎．群决策监督模糊模式识别模型[J]．控制与决策，2002，17(增)：672～675
[130] 元继学，吴祈宗，于向军．基于Bonissone近似算法的群决策方法[J]．数 学的实践与认识，2003，33(12)：66～71
[131] 樊治平，姜艳萍，肖四汉．基于OIYA算子的不同形式偏好信息的群决策方法[J]．控制与决策，2001，16(增)：749～752
[132] 周珍，吴祈宗，刘福祥．三角模糊数互补判断矩阵的一种排序方法及其在项目投资决策中的应用[J]．数学的实践与认识，2005，35(11)：74～77
[133] 徐玖平．基于Hausdorff度量模糊多指标群决策的TOPSIS方法[J]．系统工程理论与实践，2002，10：84～93
[134] 吕大刚，王力，张鹏，光远．模糊多属性决策的相似接近度解法[J]．控制与决策，2004，19(11)：1282～1285
[135] 兰继斌，徐扬，刘家忠．模糊多属性决策的折衷方法[J]．系统工程与电子技术，2004，26(1)：40～43
[136] 李荣钧．模糊决策的基础：模糊集比较与排序[J]．控制与决策，2003，18(2)：221～224
[137] 何亚群，胡寿松．一种基于粗糙模糊集成模型的决策分析方法[J]．控制与决策，2004，19(3)：315～318
[138] 彭怡，胡杨，郭耀煌．基于群体理想解的多属性群决策算法[J]．西南交通大学学报，2003，38(6)：682～685
[139] 夏勇其，吴祈宗．一种混合型多属性决策问题的TOPSIS方法[J]．系统工程学报，2004，19(6)：630～634
[140] 于春海，樊治平．一种基于群体语言相似矩阵的聚类方法[J]．系统工程，2004，22(7)：76～79
[141] 徐章艳，尹云飞．一种区间值聚类的数据挖掘方法[J]．系统工程与电子技术，2005，27(3)：565～567
[142] 江文奇，华中生．一种改进的群体效用集结方法[J]．系统工程与电子技术，2005，27(2)：253～256
[143] J. Claussen, A. Kemper, D. Kossmann, C. Wiesner. Exploiting Early Sorting and Early Partitioning for Decision Support Query Processing[J]. The VLDB Journal, 2000, 9:190～213
[144] Soung Hie Kim, Sang Hyun Choi, Jae Kyeong Kim. An Interactive Procedure for Multiple Attribute Group Decision Making With Incomplete Information: Range-based Approach[J]. European Journal of Operational Research, 1999, 118: 139～152
[145] Takehiro Inohara. Cluster Ability of Groups and Information Exchange in Group Decision Making with Approval Voting System[J]. Applied Mathematics and Computation, 2003, 136: 1～15
[146] Fo Herrera, E. Herrera-Viedma, J. L. Verdegay. AModel of Consensus in Group Decision Making under Linguistic Assessments[J]. Fuzzy Sets and Systems, 1996, 78: 73～87
[147] Sajjad Zahir. Clusters in a Group: Decision Making in the Vector Space Formulation of the Analytic Hierarchy Process[J]. European Journal of Operational, 1999, 112:620～634
[148] Chen Xiaohong, Lai Bangchuan, Luo Ding. Mining Association Rule Eff iciently Based on Data Warehouse[J]. Cent. South univ. Technol, 2003, 10: 375～380
[149] 高峰记，黄咏芳，任晓燕．多指标区间决策的理想点贴近法[J]．数学的实践与认识，2005，35(1)：30～33
[150] 徐泽水，达庆利．区间型多属性决策的一种新方法[J]．东南大学学报自然科学版，2003，33(4)：498～501
[151] 王爱玲．群决策方法研究[J]．统计与决策，2002，4：29～31
[152] 樊治平，李洪燕，姜艳萍．基于OWA算子的群决策方法的灵敏度分析[J]．东北大学学报自然科学版，2004，25(11)：1114～1117
[153] 王坚强．一种新的有优序综合评价的群决策方法[J]．系统工程与电子技术，2002，24(8)：21～23
[154] 宋光兴，邹平．多属性决策的群排序方法研究[J]．运筹与管理，2002，11(3)：27～31
[155] 徐泽水．基于方案达成度和综合度的交互式多属性决策法[J]．控制与决策，2002，17(4)：435～438
[156]姜灵敏，陈松乔．一种基于模糊聚类分析的综合排序算法[J]．计算机工程与应用，2003，36：90～92
[157] 曹荣增，李一军．一种基于偏好分布的群决策方法[J]．管理工程学报，2004，18(3)：121～124
[158] Gungor, Z., Arikan, F. A Fuzzy Outranking Method in Energy Policy Planning[J]. Fuzzy Sets and Systems, 2000, 58 (4): 114～122
[159] Ljubisa vlacic, Michio amagasa. Applying Multi-Attribute-bases Group Decision Making Techniques in Complex Equipment Selection Tasks[J]. Group Decision and Negotiation, 1997, 6: 529～556
[160] 陈建军，杨振山．基于智能体和数据仓库的群决策支持系统[J]．微机发展，2004，14(1)：1～3
[161] Korhonen. P., Moskowitz. H., Wallenius. J.. Multiple Criteria Decision Support: A Review[J]. European Journal of Opemtional Research, 1992, 63: 361～375
[162] T．X．Bui著，席酉民，侯宁霞译．群体决策支持系统[M]．西安：西安交通大学出版社，1992
[163] 卓越等．群决策支持系统中的一致性分析技术[J]．控制与决策，1999，14(6)：636～641
[164] 俞伟，陈学广．群件对群决策支持系统性能影响的研究[J]．兵工自动化，2003，22(1)：1～3
[165] 李必强，胡浩．系统集成数据仓库与模糊群决策理论的决策支持系统[J]．武汉理工大学学报信息与管理工程版，2004，26(6)：21～23
[166] 徐选华，陈晓红．基于Multi-Agent的决策支持系统模型管理研究[J]．计算机工程与应用，2005，13：194～196
[167] 徐选华，陈晓红．群体决策支持系统的模型库研究[J]．中南大学学报社会科学版，2003，9(4)：505～507
[168] 陈晓红，周艳菊．基于遗传算法的群体决策支持系统有效性的评价[J]．系统工程，2001，19(6)：55～58
[169] 陶庆，王威．决策支持系统的模糊综合评价[J]．数学的实践与认识，2005，35(5)：71～79
[170] 陈晓红，周艳菊．基于层次模型法的互联网环境下的群体决策支持系统[J]．中国管理科学，2001，9(6)：49～57
[171] 翟丽丽．基于Internet的多属性评价群决策支持系统总体设计[J]．哈尔滨理工大学学报，2004，9(1)：69～71
[172] 张相斌，杨德礼．基于多属性的系统结构建模与分析方法[J]．系统工程理论方法应用，2002，11(2)：146～152
[173] Reay-Chen Wang, Shian-Jong Chuu. Group Decision-making Using a Fuzzy Linguistic Approach for Evaluating the Flexibility in a Manufacturing System[J]. European Journal of Operational Research, 2004, 154: 563～572
[174] Datta A, Thomas H. The Cube Data Model: a Conceptual Model and Algebra for On-line Analytical Processing in Data Warehouses[J]. Decision Support Systems, 1999, 27(3): 289～301
[175] Ruspini E H. A New Approach to Clustering[J]. Fuzzy sets and systems, 1969, 15(1): 22～32
[176] Tamra S, et al. Pattern Classification Based on Fuzzy Relations[J]. IEEE Trans SMC, 1971, 1(1): 217～242
[177] Backer E, Jain A K. A Clustering Performance Measure Based on Fuzzy Set Decomposition[J]. IEEE Trans PAMI, 1981, 3(1): 66～74
[178] Dunn J C. A Graph Theoretic Analysis of Pattern Classification via Tamura's Fuzzy Relation[J]. IEEE Trans SMC, 1974, 4(3): 310～313
[179] Matula D W. Graph Theoretic Techniques for Cluster Analysis Algorithms[A]. In: J Van Ryzin. Proceedings of the Advanced Seminar on Classification and Clustering[C]. New York: Academic Society, 1977. 95～129
[180] Bezdek J C, Harris J O. Convex Decompositions of Fuzzy Partitions[J]. IEEE Trans on JMAA, 1979, 67: 490～512
[181] Esogbue A O. Optimal Clustering of Fuzzy Data via Fuzzy Dynamic Programming[J]. FSS, 1986, 18: 283～298
[182] Mantaras R L D, Valverde L. New Results in Fuzzy Clustering Based on the Concept of Indistinguishably Relation[J]. IEEE Trans on PAMI, 1988, 10(5): 754～757
[183] Duda R O, Hart P E. Pattern Classification and Scene Analysis[J]. New York: John Wiley& Sons Press, 1973
[184] Dunn J C. Well-Separated Clusters and the Optimal Fuzzy Partitions[J]. Fuzzy Sets and Systems, 1974, 4(1): 95～104
[185] Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms[M]. New York: Plenum Press, 1981
[186] Bezdek J C. A Convergence Theorem for the Fuzzy Isodata Clustering Algorithm[J]. IEEE Trans on PAMI, 1980, 1(2): 1～8
[187] 赵恒，杨万海．基于属性加权的模糊K-Modes聚类算法[J]．系统工程与电子技术，2003，25(10)：1229～1302
[188] Bezdek JC. Clustering Validity with Fuzzy Sets[J]. Journal of mathematical biology, 1974, 22(1): 57～71
[189] 王连亮，陈怀新．基于改进的模糊C-均值的分级递减聚类算法[J]．系统工程与电子技术，2005，27(7)：1304～1306
[190] 孔锐，张国宣，施泽生，郭立．基于核的K-均值聚类[J]．计算机工程， 2004，30(11)：12～13
[191] 刘纪平，汪宏斌，汪诚波，周洞汝．基于模糊最近邻的高维数据聚类[J]．小型微型计算机系统，2005，26(2)：261～263
[192] 张曙红，孙建勋，诸克军．基于遗传优化的采样模糊C均值聚类算法[J]．系统工程理论与实践，2004，5：121～125
[193] 陈晓红，秦杨．基于映射簇的Web数据挖掘研究[J]．系统工程，2004，22(7)：80～83
[194] 沈红斌，王士同，吴小俊．离群模糊核聚类算法[J]．软件学报，2004，15(7)：1021～1029
[195] 张新波．两阶段模糊C-均值聚类算法[J]．电路与系统学报，2005，10(2)：117～120
[196] 李侃，刘玉树．模糊核聚类的自适应算法[J]．控制与决策，2004，19(5)：595～597
[197] Panayirc E. A Test for Multidimensional Clustering Tendency[J]. Pattern Recognition, 1983, 16(4): 434～444
[198] 诸克军，苏顺华，黎金玲．模糊C-均值中的最优聚类与最佳聚类数[J]．系统工程理论与实践，2005，3：52～61
[199] 于春海，樊治平．一种基于区间数多指标信息的FCM聚类算法[J]．系统工程学报，2004，19(4)：387～393
[200] 李洁，高新波，焦李成．一种基于修正划分模糊度的聚类有效性函数[J]．系统工程与电子技术，2005，27(4)：723～726
[201] 王元珍，王健，李晨阳．一种改进的模糊聚类算法[J]．华中科技大学学报(自然科学版)，2005，33(2)：92～94
[202] 陈晓红，刘蓉．改进的聚类算法及在复杂大群体决策中的应用[J]．系统工程与电子技术(已录用)
[203] Liu Rong, Chen Xiaohong. Continuous Trust Building Methods Basing on Cluster-Head in VE[A]. Proceedings of the 5rdWuhan International Conference on E-Business[C]. Wuhan, China, 2006
[204] 刘蓉．数据挖掘及其在通信企业经营分析领域的应用[J]．科技进步与对策，2004，10：159～161
[205] 蒋长浩．图论与网络流[M]．北京：中国林业出版社，2001．21～35，98～119
[206] M. L. Garey, D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness[M]. San Francisco: W. H. Freeman, 1979
[207] Sudipto Guha, Samir Khuller. Approximation Algorithms for Connected Dominating Sets[A]. Proceedings of the 4rdAnnual European Symposium on Algorithms[C]. Barcelona: The Fourth Annual European Symposium, 1996
[208] Mullen B, Anthony T, Salas E. Group Cohesiveness and Quality of Decision Making: An Integration of Tests of the Group Think Hypotheses[J]. Small Group Research, 1994, (25): 189～204
[209] Kevin Tasa, Glen Whyte. Collective Efficacy and Vigilant Problem Solving in Group Decision Making: A Non-Linear Model[J]. Organizational Behavior and Human Decision Processes, 2005, (96): 119～129
[210] ELIZABETH M. JAKOB. Individual Decisions and Group Dynamics: Why Policed Spiders Join and Leave Groups[J]. Animal behavior, 2004, (68): 9～20
[211] Wheelan S, Hochberger J. Validation Studies of the Group Development Questionnaire[J]. Small Group Research, 1996, 27(1): 143～170
[212] 毕鹏程，席酉民，王益谊．群体发展过程中的群体思维演变研究[J]．预测，2005，24(3)：1～7
[213] Wheelan S. Facilitating Training Groups: A Guide to Leadership and Verbal Intervention Skills[J]. Small Group Research, 1990
[214] Wheelan S. Group Processes: A Developmental Perspective[M]. Boston: Ally & Bacon, 1994
[215] Michael R., Baumann, Bryan L. Bonner. The Effects of Variability and Expectations on Utilization of Member Expertise and Group Performance[J]. Organizational Behavior and Human Decision Processes, 2004, 93: 89～101
[216] 柯年满，王重鸣．多层次团队决策理论及其进展[J]．心理科学，2003，26(3)：527～528
[217] 毕鹏程，郎淳刚，席酉民．领导风格和行为对群体决策过程和结果的影响[J]．西安交通大学学报(社会科学版)，2005，25(2)：1～10
[218] William Schiano, Joseph W. Weiss. Y2K All Over Again: How Groupthink Permeates and Compromises Security[J]. Business Horizons, 2006, 49: 115～125
[219] Sarwar B, Karypis G, Konstan J et al. Item-based Collaborative Filtering Recommendation Algorithms[A]. Proceedings of the 10rdinternational World Wide Web Conference[C]. Houston, 2001. 285～295
[220] 邓爱林，朱扬勇，施伯乐等．基于项目评分预测的协同过滤推荐算法[J]．软件学报，2003，14(9)：1621～1628
[221] 徐仲．矩阵论简明教程[M]．北京：科学出版社，2002
[222] 侯如成，陈守煜．水库防洪调度多目标模糊群决策方法[J]．水利学报，2004，12．106～111
[223] 王熙照，王亚东等．学习特征权值对K-均值聚类算法的优化[J]．计算机研究与发展，2003，40(6)：869～873
[224] D S Yeung, E C C Tsang. Weighted Fuzzy Production Rules[J]. Fuzzy Sets and Systems, 1997, 88: 299～313
[225] J Basak, R K De, S K Pal. Unsupervised Feature Selection Using A Neuron-Fuzzy Approach[J]. Pattern Recognition Letters, 1998, 19(11): 997～1006
[226] 倪国熙．常用的矩阵理论和方法[M]．上海：上海科学技术出版社，1984．176
[227] Reimnt B, Robert G. Supporting Group Decision Process With Software Agents[A]. Proceedings of the 3rdIS-DSS Conference[C]. Hong Kong, 1995.
[228]David Hand等．Printiples of Data Mining(数据挖掘原理)[M]．北京：机械工业出版社，2003
[229] 周磊．中国在线消费者对在线营销者信任问题的实证研究[博士学位论文]．上海：复旦大学，2005
[230] Fishbein, M and Ajzen I. Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research[J]. Addison-Wesley, Reading, 1975, 12: 36～39