兵工自动化2011，Vol.30Issue(11)：43-46,4.DOI:10.3969/j.issn.1006-1576.2011.11.012
基于混沌理论和BP神经网络的某基地电力短期负荷预测
Short-Term Load Forecasting of Navy Certain Base Based on Chaotic Time Series and Artificial Neural Networks
宋振宇 1谭勖 2刘宇 3邵阳3
作者信息
- 1. 海军航空工程学院科研部,山东烟台264001
- 2. 海军航空工程学院研究生管理大队,山东烟台264001
- 3. 中国人民解放军92330部队,山东青岛266102
- 折叠
摘要
Abstract
In order to rationally arrange and give priority to ensuring the power dispatching problem of a military base, a method of shot-term load forecasting based on chaotic time series and artificial neural networks is presented. According to chaos theory and neural networks method, it is based on the delay coordinates phase space reconstruction first, choose time delay 'τ ' and embedding dimension 'm ' by using the method of mutual information and saturation correlation dimension after, then use the BP neural networks prediction, carry out an experimental simulation about grid in the period of load sequence on a base finally. The simulation results show that the relative errors is within 5%, and 33.3% of the error is less than 1%, proved that the prediction method has higher forecasting precision and application value.关键词
混沌时间序列/BP神经网络/短期负荷预测Key words
chaotic time series/ shot-term load forecasting/ artificial neural network分类
军事科技引用本文复制引用
宋振宇,谭勖,刘宇,邵阳..基于混沌理论和BP神经网络的某基地电力短期负荷预测[J].兵工自动化,2011,30(11):43-46,4.
