Research on A Genetic Neural Artificial Network in Short Term Load Forecasting

摘要：

Short-term load forecasting is one of the most important contents of running and dispatching power system. In order to avoid the limitation of the BP neural networks and improve the efficiency and the accuracy of forecasting,this paper established the short-term load forecasting based on the Genetic Neural Artificial Network. The model mended the activation function,introduced the momentim item and made use of GA to confirm the parameters of the networks. The example showed that this model can effectively improve the forecasting precision.

关键词： Short-term load forecasting the Genetic Neural Artificial Network the activation function the momentim item

作者: WANG Luchao DENG Yongping

作者单位: Water Resource and Hydropower College Wuhan University Wuhan, Hubei Province, China Guangzhou Research and Development Center China Telecom Guangzhou, Guangdong Province, China

会议类型: 国际会议

会议名称: 第一届国际计算机新科技与教育学术会议(Proceedings of the First International Conference on Computer Science & Education ICCSE2006)

会议地点: 厦门

会议语种:英文

页码: 823-825

在线出版日期: 2006-07-27（万方平台首次上网日期，不代表论文的发表时间）