Research on RS-WNN Integrated Modeling

Zong Chang Xu; Xue Qin Tang; Shu Feng Huang

doi:10.4028/www.scientific.net/AMM.105-107.2169

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 105-107Research on RS-WNN Integrated Modeling

Research on RS-WNN Integrated Modeling

Abstract:

Wavelet Neural Network (WNN) integration modeling based on Rough Set (RS) is studied. An integration modeling algorithm named RS-WNN, which first introduces a heuristic attribute reduction recursion algorithm to determine the optimum decision attributes and then conducts WNN modeling, is proposed. This method is adopted to more effectively eliminate the redundant attributes, lower the structure complexity of WNN, which reduce the time of training and improve the generalization ability of WNN. The result of the experiment shows this method is superior and efficient.

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Periodical:

Applied Mechanics and Materials (Volumes 105-107)

Pages:

2169-2173

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.105-107.2169

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Online since:

September 2011

Authors:

Zong Chang Xu, Xue Qin Tang, Shu Feng Huang

Keywords:

Attribute Reduction, Integration Modeling, Rough Set (RS), Wavelet Neural Network (WNN)

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