The Effect of Several Parameters on Radial Basis Function Networks for Time Series Prediction | Zendy

Mitat Uysal | Zendy

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The Effect of Several Parameters on Radial Basis Function Networks for Time Series Prediction

Author(s) -

Mitat Uysal

Publication year - 2006

Publication title -

journal of applied sciences

Language(s) - English

Resource type - Journals

eISSN - 1812-5662

pISSN - 1812-5654

DOI - 10.3923/jas.2006.1608.1611

Subject(s) - series (stratigraphy) , radial basis function , radial basis function network , time series , function (biology) , computer science , artificial intelligence , artificial neural network , machine learning , geology , paleontology , evolutionary biology , biology

In this study, several radial basis function networks are compared according to their approximation ability in time series forecasting problems. Optimal values for the tested parameters are obtained using computer simulation runs. Effects of width selection in Gaussian Kemels, of the number of neurons in the hidden layer, and of selection of Kemel function are investigated

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