Energy Demand Forecasting Based on Economy-related Factors in China

被引：7

作者：

Cao, Z. ^{[1
]}

Yuan, P. ^{[1
]}

Ma, Y. B. ^{[1
]}

机构：

[1] Sichuan Univ, Coll Water Resource & Hydropower, Chengdu 610065, Peoples R China

来源：

ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY | 2014年 / 9卷 / 02期

关键词：

China; energy demand; forecasting; inputs; model; PARTICLE SWARM OPTIMIZATION; GA;

D O I：

10.1080/15567249.2013.790521

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：

Energy plays an extremely important role in economic growth in modern society. The significance is self-evident in energy resources planning and management due to the continuing increase in worldwide diminishing accessibility of energy resources. An increasing number of publications show that energy demand is strongly related to economy development. In order to analyze the energy demand in the future, previous studies employing a variety of models through different inputs for energy demand forecasting in China have been proposed. This article develops an energy demand forecasting model by combining support machine regression and quantum-behaved particle swarm optimization as it adopts eight economy-related inputs. It indicates that the proposed model is superior to some of the popular models in energy demand forecasting in China.

引用

页码：214 / 219

页数：6

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