Intelligent Computing and Applications by Durbadal Mandal Rajib Kar Swagatam Das & Bijaya Ketan Panigrahi

Author:Durbadal Mandal, Rajib Kar, Swagatam Das & Bijaya Ketan Panigrahi
Language: eng
Format: epub
Publisher: Springer India, New Delhi

2 Proposed Adaptive Neuro-Fuzzy Inference System

2.1 Fuzzy Logic System

Fuzzy set theory was developed by Prof. L.A. Zadeh [9] to capture the imprecise modes of reasoning employed in an environment characterized by uncertainty and vagueness. A fuzzy inference system employing fuzzy ‘if-then’ rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analysis. This fuzzy modeling first explored systematically by Takagi and Sugeno [10]. A fuzzy inference system is composed of a rule base, containing a number of fuzzy if-then rules; a database, which defines the membership functions of fuzzy sets used in fuzzy rules; a decision-making unit which performs inference operations on the rules; and a defuzzification interface, which transforms fuzzy results into a crisp output. The integration of neural network into fuzzy logic system makes it possible to learn from data prior.

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