An Efficient Algorithm to Computing Max–Min Inverse Fuzzy Relation for Abductive Reasoning

This paper provides an alternative formulation to computing the max-min inverse fuzzy relation by embedding the inherent constraints of the problem into a heuristic (objective) function. The optimization of the heuristic function guarantees maximal satisfaction of the constraints, and consequently, the condition for optimality yields solution to the inverse problem. An algorithm for computing the max-min inverse fuzzy relation is proposed. An analysis of the algorithm indicates its relatively better computational accuracy and higher speed in comparison to the existing technique for inverse computation. The principle of fuzzy abduction is extended with the proposed inverse formulation, and the better relative accuracy of the said abduction over existing works is established through illustrations with respect to a predefined error norm.

[1]  Masaki Togai OF A FUZZY CONTROLLER FOR DYNAMIC SYSTEMS , 1984 .

[2]  Costas P. Pappis Multi-input multi-output fuzzy systems and the Inverse Problem , 1987 .

[3]  Salvatore Sessa,et al.  On the set of solutions of composite fuzzy relation equations , 1983 .

[4]  Mattias Krysander,et al.  An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[5]  Krishna R. Pattipati,et al.  Dynamic Multiple Fault Diagnosis: Mathematical Formulations and Solution Techniques , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[6]  S. Sessa Some results in the setting of fuzzy relation equations theory , 1984 .

[7]  Shun'ichi Tano,et al.  The inverse Problem of the Aggregation of fuzzy Sets , 1994, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[8]  Elie Sanchez,et al.  Resolution of Composite Fuzzy Relation Equations , 1976, Inf. Control..

[9]  M. Miyakoshi,et al.  Solutions of composite fuzzy relational equations with triangular norms , 1985 .

[10]  L. A. Zedeh Knowledge representation in fuzzy logic , 1989 .

[11]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[12]  A. Lettieri,et al.  Characterization of some fuzzy relation equations provided with one solution on a finite set , 1984 .

[13]  Fred W. Roush,et al.  Generalized fuzzy matrices , 1980 .

[14]  Amit Konar,et al.  Computational Intelligence: Principles, Techniques and Applications , 2005 .

[15]  Irina Perfilieva,et al.  COMPATIBILITY OF SYSTEMS OF FUZZY RELATION EQUATIONS , 2000 .

[16]  Shun'ichi Tano,et al.  Backward-chaining with fuzzy 'if. . . then. . .' rules , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[17]  Jiranut Loetamonphong,et al.  An efficient solution procedure for fuzzy relation equations with max-product composition , 1999, IEEE Trans. Fuzzy Syst..

[18]  Shu-Cherng Fang,et al.  Solution Sets of Interval-Valued Fuzzy Relational Equations , 2003, Fuzzy Optim. Decis. Mak..

[19]  Da Ruan,et al.  Novel neural algorithms based on fuzzy δ rules for solving fuzzy relation equations: Part I , 1997, Fuzzy Sets Syst..

[20]  D. Grant Fisher,et al.  Solution algorithms for fuzzy relational equations with max-product composition , 1998, Fuzzy Sets Syst..

[21]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[22]  W. Pedrycz Fuzzy relational equations with generalized connectives and their applications , 1983 .

[23]  E. Sanchez Solution of fuzzy equations with extended operations , 1984 .

[24]  H. Zimmermann,et al.  Fuzzy Set Theory and Its Applications , 1993 .

[25]  Edward A. Bender,et al.  Mathematical methods in artificial intelligence , 1996 .

[26]  Kevin Knight,et al.  Artificial intelligence (2. ed.) , 1991 .

[27]  Wen-June Wang,et al.  Matrix-pattern-based computer algorithm for solving fuzzy relation equations , 2003, IEEE Trans. Fuzzy Syst..

[28]  Siegfried Gottwald,et al.  Generalized solvability criteria for fuzzy equations , 1985 .

[29]  W Pedrycz,et al.  Solvability of fuzzy relational equations and manipulation of fuzzy data , 1986 .

[30]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[31]  Lotfi A. Zadeh,et al.  Knowledge Representation in Fuzzy Logic , 1996, IEEE Trans. Knowl. Data Eng..

[32]  W. Pedrycz,et al.  Fuzzy relation equations on a finite set , 1982 .

[33]  W. Pedrycz Inverse problem in fuzzy relational equations , 1990 .

[34]  Jian-Xin Li,et al.  Fuzzy relation inequalities about the data transmission mechanism in BitTorrent-like Peer-to-Peer file sharing systems , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.

[35]  Shun'ichi Tano,et al.  Interval-valued fuzzy backward reasoning , 1995, IEEE Trans. Fuzzy Syst..

[36]  M. Prévot Algorithm for the solution of fuzzy relations , 1981 .

[37]  M. Sugeno,et al.  Fuzzy relational equations and the inverse problem , 1985 .

[38]  Chi-Tsuen Yeh,et al.  On the minimal solutions of max-min fuzzy relational equations , 2008, Fuzzy Sets Syst..

[39]  Amit Konar,et al.  A heuristic algorithm for computing the max-min inverse fuzzy relation , 2002, Int. J. Approx. Reason..

[40]  Józef Drewniak,et al.  Fuzzy relation equations and inequalities , 1984 .

[41]  G. Klir,et al.  Resolution of finite fuzzy relation equations , 1984 .

[42]  Amit Konar,et al.  Emotion Recognition From Facial Expressions and Its Control Using Fuzzy Logic , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[43]  C. Pappis,et al.  A computer algorithm for the solution of the inverse problem of fuzzy systems , 1991 .

[44]  Jianmiao Cen Fuzzy matrix partial orderings and generalized inverses , 1999, Fuzzy Sets Syst..

[45]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[46]  Da Ruan,et al.  Novel neural algorithms based on fuzzy δ rules for solving fuzzy relation equations: Part III , 2000, Fuzzy Sets Syst..

[47]  Yan-Kuen Wu,et al.  An Efficient Procedure for Solving a Fuzzy Relational Equation With Max–Archimedean t-Norm Composition , 2008, IEEE Transactions on Fuzzy Systems.