TITLE:
A t-Norm Fuzzy Logic for Approximate Reasoning
AUTHORS:
Alex Tserkovny
KEYWORDS:
Fuzzy Logic, t-Norm, Implication, Antecedent, Consequent, Modus-Ponens, Fuzzy Conditional Inference Rule
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.10 No.7,
June
29,
2017
ABSTRACT: A t-norm fuzzy logic is presented, in which a triangular norm (t-norm) plays the role of a graduated conjunction operator. Based on this fuzzy logic we develop methods for fuzzy reasoning in which antecedents and consequents involve fuzzy conditional propositions of the form “If x is A then y is B”, with A and B being fuzzy concepts (fuzzy sets). In this study, we present a systemic approach toward fuzzy logic formalization for approximate reasoning. We examine statistical characteristics of the proposed fuzzy logic. As the matter of practical interest, we construct a set of fuzzy conditional inference rules on the basis of the proposed fuzzy logic. Important features of these rules are investigated.