Forecasting Chinese Energy Supply and Demand Situation with BP Neural Network

被引：2

作者：

Zhang, Linyun ^{[1
]}

Li, Jinchang ^{[1
]}

机构：

[1] Zhejiang Gongshang Univ, Sch Math & Stat, Hangzhou, Zhejiang, Peoples R China

来源：

SUSTAINABLE DEVELOPMENT OF INDUSTRY AND ECONOMY, PTS 1 AND 2 | 2014年 / 869-870卷

关键词：

BP neural network; Energy supply and demand; Prediction;

D O I：

10.4028/www.scientific.net/AMR.869-870.541

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper utilizes back propagation (BP) neural network to make a prediction to a number of Chinese energy supply and demand indictors during the years of 2000 and 2011, and acquires the supply and demand as well as insufficiency percentage of Chinese total energy supply and demand, raw coal, crude oil, natural gas, hydropower, nuclear power, wind power, and generating capacity from 2012 to 2025, from which it is found out that the total energy is still on the stage of short supply, where traditional energy such as coal and oil will decrease, and be replaced by new energy including natural gas, hydropower, nuclear power, wind power, and so forth.

引用

页码：541 / 544

页数：4

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