Chinese Annual Electric Power Consumption Forecasting Based on Grey Model and Global Best Optimization Method

被引：0

作者：

Meng, Ming ^{[1
]}

Shang, Wei ^{[2
]}

机构：

[1] North China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R China

[2] Sch Econ Hebei Univ, Baoding 071002, Hebei, Peoples R China

来源：

FIRST INTERNATIONAL WORKSHOP ON DATABASE TECHNOLOGY AND APPLICATIONS, PROCEEDINGS | 2009年

关键词：

Chinese annual electric power consumption; forecasting; grey model; global best optimization method; NEURAL-NETWORKS;

D O I：

10.1109/DBTA.2009.126

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The annual electric power consumption is one of the most important factors in operation decisions of Chinese electric power generation groups. The grey model is feasible method to deal with this trend extension problem with few data. But the simple approximation in dispersing the first order differential equation affects it forecasting precise. Based on adjusting the positions of each particle, the global best optimization method could search the best proportion point. This could improve the forecasting results in the practice of annual electric power consumption.

引用

页码：677 / +

页数：2

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