Recent advances in neuro-fuzzy system: A survey

Abstract Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific and engineering areas due to its effective learning and reasoning capabilities. The neuro-fuzzy systems combine the learning power of artificial neural networks and explicit knowledge representation of fuzzy inference systems. This paper proposes a review of different neuro-fuzzy systems based on the classification of research articles from 2000 to 2017. The main purpose of this survey is to help readers have a general overview of the state-of-the-arts of neuro-fuzzy systems and easily refer suitable methods according to their research interests. Different neuro-fuzzy models are compared and a table is presented summarizing the different learning structures and learning criteria with their applications.

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