The Short-Term Gas Load Forecasting Using The Combination Method Based On Wavelet

摘要：

The prediction of gas load is an essential indicator for the Gas supply system to make their strategies.recently,many researchers focus on how to combine some forecast methods to enhance the accuracy.This paper is to advance a new method that first abstract the available characters from the complex sources of information by the wavelet analysis,then search for the best way to get several individual forecast method combined,called CFBOW (combination forecast based on wavelet).So that effectively improves the accuracy of the prediction.The result improves the forecast performance that brings up large interests to the Gas supply system.

关键词： BP neural network grey theory time series,wavelet gas load forecasting

作者: Li Zhang Xiaozhong Xu

作者单位: information,mechanical and electrical engineering college of shanghai normal university S.H.N.U. Sha information,mechanical and electrical engineering college of shanghai normal university S.H.N.U. Sha

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 279-283

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）