Date of Publication :20th November 2023

Abstract: Numerous problems can be resolved by genetic fuzzy systems in a variety of application areas. In this study, we attempt to integrate the learning and adapting characteristics if genetic algorithms with fuzzy systems. To identify the most effective alternative approach, we are utilizing optimization methods that combine fuzzy theory and genetic algorithms. Specifically, our paper provides an overview of genetic fuzzy systems, with a focus on genetic fuzzy rule-based systems. This study aims to explore novel strategies for incorporating genetic evolutionary techniques into a fuzzy rule-based system. While machine learning approaches have shown potential in enhancing fuzzy rules, the development of systematic methods for this integration has been lacking until recently. Consequently, machine learning technologies can significantly contribute to the improvement of fuzzy rule systems. In this paper we will try to analyses the new perspective for machine learning concepts.

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