Genetic algorithms play a significant role, as search techniques forhandling complex
spaces, in many fields such as artificial intelligence, engineering, robotic, etc. Genetic …

The purpose of this paper is to present a genetic learning process for learning fuzzy control
rules from examples. It is developed in three stages: the first one is a fuzzy rule genetic …

This paper shows how knowledge, in the form of fuzzy rules, can be extracted from a fuzzy
neural network. A genetic algorithm is applied to find near-optimal fuzzy rules and learn the …

This paper presents a novel evolutionary tuning method that adapts the knowledge base of
a fuzzy logic controller. The evolution strategy adopted in this paper employs a variable size …

In this paper, we deal with the problem of computing the maintenance costs of electrical
medium line in spanish towns. To do so, we present two Data Analysis tools taking as a …

The single input rule modules (SIRMs) connected inference model is a fuzzy inference
model in which a single input rule module is constructed for each system input variable. The …

The electronic and· spatial data revolution of the last two decades has resulted in the
development of a variety of data-management tools for handling the vast amounts of …