Conference paper
Scheduling exploration/exploitation levels in genetically-generated fuzzy knowledge bases
In this paper we study the influence of the exploration/exploitation balance on the performances of a real binary/like coded genetic algorithm in automatically generating fuzzy knowledge bases from a set of numerical data. The influence is explored through different scheduling of crossover strategies throughout the evolution process.
The aim is to prove the influence of a good balance between exploration and exploitation levels on the performances of the optimization algorithm, along with the influence of a good definition of the early versus late stages of the evolution.
| Language: | English |
|---|---|
| Year: | 2004 |
| Pages: | 401,402,403,404,405,406 |
| Proceedings: | NAFIPS 2004. 2004 Annual Meeting of the North American Fuzzy Information Processing Society |
| ISBN: | 0780383761 and 9780780383760 |
| Types: | Conference paper |
| DOI: | 10.1109/NAFIPS.2004.1336316 |
Decision making Decision support systems Ear Evolution (biology) Fuzzy logic Fuzzy sets Genetic algorithms Mechanical engineering Stochastic processes Testing automatically generating fuzzy knowledge bases binary codes crossover strategies decision support systems evolution process exploration-exploitation balance fuzzy decision support system fuzzy logic fuzzy set theory genetic algorithms genetically generated fuzzy knowledge bases knowledge based systems optimization algorithm real binary-like coded genetic algorithm scheduling
