A Time Prediction Method Using Modified Neural Network

Yu Kun Zhang; Shu He; Yong Jun Cheng

doi:10.4028/www.scientific.net/AMR.1044-1045.1023

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1044-1045A Time Prediction Method Using Modified Neural...

A Time Prediction Method Using Modified Neural Network

Abstract:

The main objective of time series analysis is to develop models that can establish the relation between variables,the paper ,An improved method of the RBF is proposed,which is a five-layered network structure comprising of an input layer,wavelet layer, product layer, output layer and polynomial regressive weight layer.which uses an online optimization approach, the method uses an offline learning method known as SNPOM,the polynomial weights are updated many times during the process of looking for the search direction to update the nonlinear parameters. The experiment showed that the optimization technique can speed up the convergence rate of nonlinear model during the learning process.

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Periodical:

Advanced Materials Research (Volumes 1044-1045)

Pages:

1023-1027

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1023

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Online since:

October 2014

Authors:

Yu Kun Zhang, Shu He, Yong Jun Cheng

Keywords:

Multiple Linear Regression, Neural Network (NN), Parameter Estimation, RBF, Time Series

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