Mathematical Theory and Applications ›› 2017, Vol. 37 ›› Issue (3-4): 78-92.
Previous Articles Next Articles
Huang Xiaofeng, Liao Lipei ,Zhu Hao
Online:
Published:
Abstract: This paper selects the typical industry data of copper and copper consumption in China in the years 1999-2015and applies the adaptive-Lasso method to analyze and identify the key industries that affect the consumption of copper in China.Based on the analysis,a combined model of grey Verhulst and BP neural net-work is constructed,and the consumption of copper in China is predicted by this model.The peak of copper consumption in China will arrive in the years 2020-2026,with a peak range of 990×104-1300×104 tons.And we suggest that the copper smelting production capacity should be controlled within 1280×104-1690× 104tons,and the new smelting investment should be suppressed so as to avoid overcapacity.
Key words: Copper consumption peak, Adaptive-Lasso, Grey, Verhulst, BP neural network
Huang Xiaofeng, Liao Lipei , Zhu Hao. Prediction of Consumption Peak of Electrolytic Copper in China Based on a Grey Verhulst-BP Neural Network[J]. Mathematical Theory and Applications, 2017, 37(3-4): 78-92.
0 / / Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: https://mta.csu.edu.cn/EN/
https://mta.csu.edu.cn/EN/Y2017/V37/I3-4/78
Research of Human Machine Identification for Sliding Verification Code Based on Neural Network
Neural Network Weight-Threshold Optimization Method Based on LASSO