An efficient algorithm to computing max-min post-inverse fuzzy relation for abductive reasoning

Authors:
Sumantra Chakraborty;Amit Konar;Ramadoss Janarthanan
Affiliations:
Artificial Intelligence Laboratory, Dept. of Electronics and Tele-Communication Engineering, Jadavpur University, Calcutta, India;Artificial Intelligence Laboratory, Dept. of Electronics and Tele-Communication Engineering, Jadavpur University, Calcutta, India;Department of IT, Jaya Engg. College, Chennai, India
Venue:
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Year:
2011

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Abstract

This paper provides an alternative formulation to computing the max-min post-inverse fuzzy relation by minimizing a heuristic (objective) function to satisfy the inherent constraints of the problem. An algorithm for computing the max-min post-inverse fuzzy relation as well as the trace of the algorithm is proposed here. The algorithm exposes its relatively better computational accuracy and higher speed in comparison to the existing technique for post-inverse computation. The betterment of computational accuracy of the max-min post-inverse fuzzy relation leads more accurate result of fuzzy abductive reasoning, because, max-min post-inverse fuzzy relation is required for abductive reasoning.