Grey RBF Neural Network Forecasting on LV under the View of Government Responsibility

Feng Rong Zhang; Annik Magerholm Fet; Xin Wei Xiao

doi:10.4028/www.scientific.net/AMR.452-453.700

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 452-453Grey RBF Neural Network Forecasting on LV under...

Grey RBF Neural Network Forecasting on LV under the View of Government Responsibility

Abstract:

At present, the domestic research on the scale of macroscopic logistics has yet belonged to the blankness, therefore, this research tries using LV in circulation and LV in stock to measure the logistics volume and forecasting it in a long period. In order to overcome the phenomenon of “floating upward” in long-term period, this paper establish the improved Grey RBF to forecast the LV next 5-10 year in Jilin province of China. The results show that the increased circulation of goods is the main reason leading to increased logistics volume, and the simulation also shows that the improved gray RBF neural network model is a good method for the government to establish the logistics development policy.

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Periodical:

Advanced Materials Research (Volumes 452-453)

Pages:

700-704

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.452-453.700

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Online since:

January 2012

Authors:

Feng Rong Zhang, Annik Magerholm Fet, Xin Wei Xiao

Keywords:

Forecast, Grey RBF, Logistics Volume (LV), Neural Network (NN)

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