Bandler, W. and Kohout, L.J. (1980) Fuzzy Relational Products as a Tool for Analysis of Complex Artificial and Natural Systems. In: Wang, P.P. and Chang, S.K., Eds., Fuzzy Sets: Theory and Applications to Policy Analysis and Information Systems, Plenum Press, New York, 311-367.

has been cited by the following article:

• 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.