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

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.

关键词： electricity consumption RBF neural network genetic algorithm prediction

作者: Zeng Qing-wei Xu Zhi-Hai Wu Jian

作者单位: Network Center Nanchang University Nanchang,China Dispatching and Communication Center Jiangxi Electric Power Company Nanchang, China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 339-342

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）