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In this paper, we describe a paradigm for learning fuzzy rules using genetic algorithms (GA). We formulate our problem of learning as follows: given a set ...
In this paper, we describe a paradigm for learning fuzzy rules using genetic algorithms (GA). We formulate our problem of learning as follows:
A methodology of learning fuzzy rules using an iterative genetic algorithm that incorporates a scheme of partitioning the entire solution space into ...
Results have shown that the GA learning approach has great potential as a tool for the learning of fuzzy control rules, particularly in situations where the ...
In our work, we propose a genetic fuzzy hybrid system that uses a genetic algorithm (GA) to directly ma-nipulate fuzzy control rules. This system uses a GA ...
The second stage employs the proposed GA based learning algorithm to identify the fuzzy rules while the final stage tunes the derived structure and parameters ...
Abstract: This paper proposes two different approaches to apply Genetic Algorithms to Fuzzy Logic Controllers whose Rule Base is defined through a set of rules.
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Nov 1, 2003 · We present a methodology of learning fuzzy rules using an iterative genetic algorithm (GA). The approach incorporates a scheme of ...
In this paper we present an approach to neuro--fuzzy classification that is able to learn fuzzy sets and fuzzy rules from data. The fuzzy rules that are ...
The main aim of this paper is to present a methodology for designing fuzzy rule-based systems from examples based on evolutionary algorithms.