An Improved Clustering Algorithm Using Fuzzy Relation for the Performance Evaluation of Humanistic Systems

A hierarchical structure is proposed for the performance evaluation of vague, complicated humanistic systems. An improved fuzzy clustering algorithm is developed to produce several partition trees with different levels and clusters according to different triangular norm compositions. Additionally, a fuzzy clustering algorithm is given to produce a partition tree without using the transitive closure composition. The usefulness of the proposed algorithm is illustrated by an example of actual academic data.

[1]  Kuo-Ming Wang,et al.  Hierarchies consistency analysis for nontransitive problems , 1996 .

[2]  Rajesh N. Davé,et al.  Generalized fuzzy c-shells clustering and detection of circular and elliptical boundaries , 1992, Pattern Recognit..

[3]  Y.-Y. Guh.  Determining weight by combining different hierarchy structures-hierarchies consistency analysis , 1996 .

[4]  Ahti Salo,et al.  Rank inclusion in criteria hierarchies , 2005, Eur. J. Oper. Res..

[5]  Flávio Sanson Fogliatto,et al.  A hierarchical method for evaluating products with quantitative and sensory characteristics , 2001 .

[6]  Miin-Shen Yang,et al.  Cluster analysis based on fuzzy relations , 2001, Fuzzy Sets Syst..

[7]  Shinichi Tamura,et al.  Pattern Classification Based on Fuzzy Relations , 1971, IEEE Trans. Syst. Man Cybern..

[8]  Gülçin Büyüközkan,et al.  A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers , 2012, Expert Syst. Appl..

[9]  Lotfi A. Zadeh,et al.  Similarity relations and fuzzy orderings , 1971, Inf. Sci..

[10]  Sylvie Chollet,et al.  Invited review Quick and dirty but still pretty good: a review of new descriptive methods in food science , 2012 .

[11]  T. Saaty.  Axiomatic foundation of the analytic hierarchy process , 1986 .

[12]  Rung-Wei Po,et al.  Establishing a multiple structures Analysis model for AHP , 2004 .

[13]  Didier Dubois,et al.  The role of fuzzy sets in decision sciences: Old techniques and new directions , 2011, Fuzzy Sets Syst..

[14]  Miin-Shen Yang,et al.  Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance , 2004, Pattern Recognit. Lett..

[15]  Saskia Janssens,et al.  Bell inequalities in cardinality-based similarity measurement , 2006 .

[16]  Ismat Beg,et al.  SIMILARITY MEASURES FOR FUZZY SETS , 2009 .

[17]  Jing-jing Ren,et al.  The Comparison about the Clustering Analysis Based on the Fuzzy Relation , 2008, ACFIE.

[18]  T. Saaty.  Highlights and critical points in the theory and application of the Analytic Hierarchy Process , 1994 .

[19]  Michael Spann,et al.  A new approach to clustering , 1990, Pattern Recognit..

[20]  D. Winterfeldt,et al.  Comparing Hierarchical and Nonhierarchical Weighting Methods for Eliciting Multiattribute Value Models , 1987 .

[21]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[22]  Miin-Shen Yang,et al.  Establishing performance evaluation structures by fuzzy relation-based cluster analysis , 2008, Comput. Math. Appl..

[23]  Peter J. Rousseeuw,et al.  Fuzzy clustering algorithms based on the maximum likelihood principle , 1991 .

[24]  Bernard De Baets,et al.  On the transitivity of a parametric family of cardinality-based similarity measures , 2009, Int. J. Approx. Reason..

[25]  Lotfi A. Zadeh,et al.  Fuzzy Logic , 2009, Encyclopedia of Complexity and Systems Science.

[26]  Hepu Deng,et al.  A Similarity-Based Approach to Ranking Multicriteria Alternatives , 2009, ICIC.

[27]  Thomas L. Saaty,et al.  Rank from comparisons and from ratings in the analytic hierarchy/network processes , 2006, Eur. J. Oper. Res..

[28]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[29]  Fuzzy Distance Measure and Fuzzy Clustering Algorithm , 2015 .

[30]  Yuh-Yuan Guh,et al.  Introduction to a new weighting method : Hierarchy consistency analysis , 1997 .

[31]  R. Bellman,et al.  Abstraction and pattern classification , 1996 .