Prediction method based on optimization theory and its application

Chen  Li; Fajie  Wei; Shenghan  Zhou

doi:10.3934/dcdss.2015.8.1213

Article Contents

2015, Volume 8, Issue 6: 1213-1221. Doi: 10.3934/dcdss.2015.8.1213

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Prediction method based on optimization theory and its application

1.
School of Economics and Management, Beihang University, Beijing 100191
2.
School of Reliability and System Engineering, Beihang University, Beijing 100191

Received: June 30, 2015

Revised: August 31, 2015

Published: November 2015

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Abstract

BP neural network is a kind of prediction method, but it has some disadvantages. So an improved particle swarm optimization scheme is used to optimize neural network parameters and structure. Both training convergence speed and classification accuracy is improved. Interest rate is always the focus in the economic research. The proposed scheme is used for seven days interbank offered rate prediction in China and the result shows that the BP neural network based on improved PSO has higher accuracy than the BP algorithm, which can provide important reference for central bank to work out monetary policy.

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Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

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