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Differential evolution and quantum-inquired differential evolution for evolving Takagi–Sugeno fuzzy models
- Source :
-
Expert Systems with Applications . Jun2011, Vol. 38 Issue 6, p6447-6451. 5p. - Publication Year :
- 2011
-
Abstract
- Abstract: The differential evolution (DE) is a global optimization algorithm to solve numerical optimization problems. Recently the quantum-inquired differential evolution (QDE) has been proposed for binary optimization. This paper proposes DE/QDE to learn the Takagi–Sugeno (T–S) fuzzy model. DE/QDE can simultaneously optimize the structure and the parameters of the model. Moreover a new encoding scheme is given to allow DE/QDE to be easily performed. The two benchmark problems are used to validate the performance of DE/QDE. Compared to some existing methods, DE/QDE shows the competitive performance in terms of accuracy. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09574174
- Volume :
- 38
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Expert Systems with Applications
- Publication Type :
- Academic Journal
- Accession number :
- 58100596
- Full Text :
- https://doi.org/10.1016/j.eswa.2010.11.107