广东石油化工学院学报2011，Vol.21Issue(6)：47-50,4.
基于粒子群优化RP网络短期电力负荷预测方法
BP Network Based on Particle Swarm Optimization of Short- term Electric Load Forecasting
姚刚 1陈政石 2李晓竹1
作者信息
- 1. 广东石油化工学院计算机与电子信息学院,广东茂名525000
- 2. 辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105
- 折叠
摘要
Abstract
As conventional BP network for the slow convergence and easy to fall into local minimum problem, the use of LM algorithm for network training, the improved particle swarm optimization BP network initial weights and threshold. Application of this method in the text grid in a city short - term load forecasting, showed that compared with conventional BP network, L- M algorithm to improve prediction models. This article describes the results of the prediction algorithm in the prediction accuracy and speed have increased greatly.关键词
电力负荷短期预测/BP网络/L—M算法/粒子群算法Key words
short- term power load forecasting/BP network/L- M algorithm/Partial Swarm Optimization Algorithm分类
信息技术与安全科学引用本文复制引用
姚刚,陈政石,李晓竹..基于粒子群优化RP网络短期电力负荷预测方法[J].广东石油化工学院学报,2011,21(6):47-50,4.
