| 一种改进的RBF网络在电力系统短期负荷预测中的应用 |
| |
| 引用本文： | 张晓亮.一种改进的RBF网络在电力系统短期负荷预测中的应用[J].煤矿机电,2008(3):90-92. |
| |
| 作者姓名： | 张晓亮 |
| |
| 作者单位： | 焦作师范高等专科学校计算机与信息工程系,河南,焦作,454000 |
| |
| 摘 要： | 针对径向基函数网络在电力系统负荷预测中隐含层节点数难求问题,提出一种改进的RBF神经网络,采用最近邻聚类学习算法自适应的调整径向基函数中心的宽度值和权值,可提高收敛速度和精度。实例仿真结果证明有效性和可行性,为电力系统负荷预测提供了一种新途径。
|
| 关 键 词： | 电力系统 负荷预测 基函数神经网络 最近邻聚类 |
Application of Improved RBF Network to Short-term Load Forecast in Electric System |
| |
| ZHANG Xiao-liang.Application of Improved RBF Network to Short-term Load Forecast in Electric System[J].Colliery Mechanical & Electrical Technology,2008(3):90-92. |
| |
| Authors: | ZHANG Xiao-liang |
| |
| Affiliation: | ZHANG Xiao-liang(Department of Computer & Information Engineering,Jiaozuo Teachers College,Jiaozuo 454000,China) |
| |
| Abstract: | In view of the difficulty in Radial Basis Function(RBF) network of load-forecast in electric system,an improved RBF neural network has been put forward.It adopts the nearest neighbor cluster learning algorithm,to self-adjust the centre-width and weight of radial basis function,in order to improve convergence speed and precision.The simulation experiment indicates its effectiveness and feasibility.The study provides a new way for load-forecast in electric system. |
| |
| Keywords: | electric system load-forecast RBF neural network nearest neighbor cluster |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
