Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6861393 | Knowledge-Based Systems | 2018 | 43 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
K.V. Shihabudheen, G.N. Pillai,