Dealing with Electrical Distribution Problems using the Fuzzy Inductive Reasoning Methodology

A. Nebot (Spain), J. Acosta (Venezuela), and P. Villar (Spain)


Electric engineering, evolutionary algorithms, genetic algorithms, fuzzy inductive reasoning, genetic fuzzy systems, machine learning.


This paper deals with the problem of estimating the maintenance cost of medium voltage lines in Spanish towns. The Fuzzy Inductive Reasoning (FIR) methodology is used for this purpose. Two genetic fuzzy systems are applied to learn the fuzzification parameters of FIR methodology, i.e. the number of fuzzy sets (classes) per variable and the membership functions. The results are compared with those obtained by other techniques such are neural networks, genetic programming and genetic fuzzy rule-base systems.

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