An overview of neural networks, fuzzy systems and neuro-fuzzy systems
Temitayo Samson Ogedengbe, Omolayo Michael Ikumapayi, Sunday Adeniran Afolalu, Adebayo T. Ogundipe, Emeka Segun Nnochiri · AIP conference proceedings · 2024
Predispositions are produced by the regular development of mixed strategies and have their roots in a variety of inventions, in this case, either in fuzzy frameworks or neural organizations.In this study, neuro-fuzzy exploration is discussed, with models provided and the neural organization point of view highlighted.The enhancement of new neural learning computations and the presentation of new fuzzy framework models could be witnessed as neuro-fuzzy exploration developed.Self-improving individuals of those new neural calculations are equipped for creating applications for the design of neuro-fuzzy frameworks from information, being a useful tool for applications and information analysis.The merging of Fuzzy Interface Systems (FIS) and Artificial Neural Networks (ANN) have drawn in the developing interest of specialists in different logical and designing regions because of the developing need for versatile savvy frameworks to take care of this present reality issue.FIS is a famous figuring system because of the idea of fuzzy theories, fuzzy guidelines, and fuzzy reasoning.ANN wins on the fly by changing the connections between layers.The upsides of a mix of FIS and ANN are self-evident.There are a few ways to deal with coordinating FIS and ANN and all the time it relies upon the application.This study comprehensively characterizes the combination of ANN and FIS into three classes which are the simultaneous model, the agreeable model, and the completely intertwined model.