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Back-propagation fuzzy system as nonlinear dynamic system identifiers
Abstract
The authors develop a training algorithm, similar to the backpropagation algorithm for neural networks, to train fuzzy systems to match desired input-output pairs. The key ideas in developing this training algorithm are to view a fuzzy system as a three-layer feedforward network, and to use the chain rule to determine gradients of the output errors of the fuzzy system with respect to its design parameters. It is shown that this training algorithm performs an error backpropagation procedure: hence, the fuzzy system equipped with the backpropagation training algorithm is called the backpropagation fuzzy system (BP FS). An online initial parameter choosing method is proposed for the BP FS, and it is shown that it is straightforward to incorporate linguistic if-then rules into the BP FS. Two examples are presented which demonstrate (1) how the fuzzy system learns to match an unknown nonlinear mapping as training progresses and (2) that performance is improved by incorporating linguistic rules.>
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Cites
Multilayer feedforward networks are universal approximators
Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728
Approximation by superpositions of a sigmoidal function
Cybenko, G. (1989) · Mathematics of Control, Signals, and Systems · doi:10.1007/bf02551274 · Cited by 13,883
Cited by
Stable adaptive fuzzy control of nonlinear systems
Wang, L.-X. (1993) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.227383 · Cited by 1,617
Self-citationGeneration of Fuzzy Rules by Mountain Clustering
Yager, R. R., & Filev, D. P. (1994) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/ifs-1994-2301 · Cited by 667
Metadata
- Authors
- Wang, L.-X., & Mendel, J. M.
- Venue
- [1992 Proceedings] IEEE International Conference on Fuzzy Systems
- Publisher
- IEEE
- Published
- 2003-01-02
- Pages
- 1409-1418
- ISSN
- 1098-7584 (ISSN-L)
- OpenAlex
- W1824237966
- Cited by
- 450
- References
- 2
- FWCI
- 13.01
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wang, L.-X., & Mendel, J. M. (2003). Back-propagation fuzzy system as nonlinear dynamic system identifiers. [1992 Proceedings] IEEE International Conference on Fuzzy Systems. https://doi.org/10.1109/fuzzy.1992.258711
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