Self-adjusted evolutionary algorithms based approach for automated design of fuzzy logic systems

A new approach to form a fuzzy logic system with evolutionary algorithms is introduced. Several algorithms were implemented as programs, efficiency measurements were made with and without self-adjustment. A new data representation method was developed for fuzzy rules base coding in genetic programming method by using reverse polish notation principle. The genetic algorithm was adapted to adjust linguistic variables semantics. The efficiency of developed algorithm was shown and compared to analogies on several test regression problems and real classification problems.