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- W2012232458 abstract "This paper presents a new version of fuzzy wavelet support vector regression machine to forecast the nonlinear fuzzy system with multi-dimensional input variables. The input and output variables of the proposed model are described as triangular fuzzy numbers. Then by integrating the triangular fuzzy theory, wavelet analysis theory and @n-support vector regression machine, a polynomial slack variable is also designed, the triangular fuzzy robust wavelet @n-support vector regression machine ([email protected]) is proposed. To seek the optimal parameters of [email protected], particle swarm optimization is also applied to optimize parameters of [email protected] A forecasting method based on [email protected] and PSO are put forward. The results of the application in sale system forecasts confirm the feasibility and the validity of the forecasting method. Compared with the traditional model, [email protected] method requires fewer samples and has better forecasting precision." @default.
- W2012232458 created "2016-06-24" @default.
- W2012232458 creator A5023927737 @default.
- W2012232458 date "2011-11-01" @default.
- W2012232458 modified "2023-09-25" @default.
- W2012232458 title "The complex fuzzy system forecasting model based on triangular fuzzy robust wavelet ν-support vector machine" @default.
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- W2012232458 doi "https://doi.org/10.1016/j.eswa.2011.04.181" @default.
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