Hybrid Models Using Artificial Neural Networks and Fuzzy Logic and Applications

Abstract

Each of the artificial intelligence techniques has unique abilities. Artificial neural networks perform computer learning by imitating human nervous system. Fuzzy logic is very close to human thinking. It can also use verbal variables. However, these techniques have their own disadvantages. The most important disadvantage of fuzzy design is that these systems do not have the ability to learn. In parallel with the advances in artificial intelligence technologies, the disadvantages of these methods have been tried to be eliminated by using these techniques together. In this study, hybrid method approaches using artificial intelligence techniques are discussed. Examples of the studies conducted in the field of social sciences using these hybrid methods are presented. Fuzzy neural networks and neural fuzzy network models are the methods that the study focuses on. It is seen that these studies have been carried out for many years. In recent years, when the variety, size and speed of data have increased, models have been proposed that give good results in different areas.