Solution to China’s GDP Prediction Problem by BP Neural Network

Guan Chen Zhou; Kai Li Wang; Tong Cui

doi:10.4028/www.scientific.net/AMM.50-51.451

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 50-51Solution to China’s GDP Prediction Problem by BP...

Solution to China’s GDP Prediction Problem by BP Neural Network

Abstract:

GDP algorithm has become the important means for China’s economic management departments to acquaint with the economic operation conditions and the important basis on which the economic development strategies and planning and various macroeconomic policies are worked out by them. Therefore, research and establishment of GDP model have an important and practical significance. In this paper, the BP neural network is adopted to perform the research and prediction of China’s GDP. Firstly, the original data of larger ones are observed and introduced into the commonly applied function of sigmoid function, but the effect is not ideal and the normalization point concentrates on , which may affect the predicted values, so a simple improvement is made for the sigmoid function to make the function value distribute between 0 and 1 and then the normalized function after improvement is better.

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Periodical:

Applied Mechanics and Materials (Volumes 50-51)

Pages:

451-454

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.50-51.451

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Online since:

February 2011

Authors:

Guan Chen Zhou, Kai Li Wang, Tong Cui

Keywords:

BP Neural Network (BPNN), GDP, Learning Rate, Sigmoid Function

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References

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