International Society of Science and Applied Technologies |
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A Dependent-Multivariate Data Analysis Method by Skewed-RBF Network Based on FGM Copula | ||||
Author | Shuhei Ota
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Co-Author(s) | Mitsuhiro Kimura
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Abstract | We extend the traditional RBF (radial basis function) network [1] to be more powerful in terms of treating the dependent input variables. For this purpose, the idea of copula [2] function is introduced. After proposing the new model, we compare the estimation performances among three models (new model, traditional RBF network, and multiple regression model) via the sample data analysis. We show the advantage of our new model by the numerical experiments.
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Keywords | FGM copula, RBF network, multiple regression analysis | |||
Article #: 21256 |
August 6-8, 2015 - Philadelphia, Pennsylvia, U.S.A. |