Prediction of Electricity Consumption Based on Genetic Algorithm - RBF Neural Network

被引：6
|
作者：
Zeng Qing-wei [1 ]
Xu Zhi-Hai [1 ]
Wu Jian [2 ]
机构：
[1] Nanchang Univ, Network Ctr, Nanchang, Peoples R China
[2] Jiangxi Elect Power Co, Dispatching & Commun Ctr, Nanchang, Jiangxi, Peoples R China
来源：
2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 5 | 2010年
关键词：
electricity consumption; RBF neural network; genetic algorithm; prediction;
D O I：
10.1109/ICACC.2010.5487062
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to avoid the economic loss due to too much or too little of electricity consumption, electricity consumption needs to be predicted. In order to solve the drawbacks of BP neural network, genetic algorithm and RBF neural network (GA-RBFNN) is presented to forecast electricity consumption in the study, and genetic algorithm is introduced and tried in optimizing the parameters of RBF neural network. The electricity consumption data and relevant features data of a certain province from September to December in 2007 are used as the experimental data. The experiment results indicate that GA-RBFNN is very suitable for electricity consumption prediction by relevant features data.
引用
收藏
页码：339 / 342
页数：4
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