Abstract
The development of neuro-fuzzy systems by integrating neural networks and fuzzy systems is desired because such systems can adjust fuzzy membership functions and produce fuzzy inference rules by case-learning without the need for experts or experiments. It has been applied to various fields, but there has been no detailed study of the various neuro-fuzzy models applicable to rule generation. In this paper, an experimentally verified five-layer and three-phase network is presented, which shows the effectiveness with which the neuro-fuzzy system automatically determines membership functions and selects activation fuzzy rules using both system identification and vibration control examples in engineering applications.
Original language | English |
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Pages (from-to) | 881-892 |
Number of pages | 12 |
Journal | Journal of Intelligent and Fuzzy Systems |
Volume | 25 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2013 Jan 1 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Engineering(all)
- Artificial Intelligence