An Efficient Algorithm to Computing Max-Min Post-inverse Fuzzy Relation for Abductive Reasoning View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Sumantra Chakraborty , Amit Konar , Ramadoss Janarthanan

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. More... »

PAGES

505-519

References to SciGraph publications

Book

TITLE

Swarm, Evolutionary, and Memetic Computing

ISBN

978-3-642-27171-7
978-3-642-27172-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-27172-4_61

DOI

http://dx.doi.org/10.1007/978-3-642-27172-4_61

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047089299


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