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投稿时间：2013-11-11
投稿时间：2013-11-11
中文摘要: 针对BP神经网络容易陷入过拟合和局部极小值的缺陷,采用殖民竞争全局优化算法,将BP神经网络的权值和阈值作为变量,并将均方差作为目标函数,组成了一种新的ICA-BP神经网络算法.结合风电厂的实际数据在Matlab平台上对该方法进行了验证,并与粒子群算法、遗传算法进行比较,得出该算法可以提高风电功率预测精度的结论.
Abstract:In view of the fact that BP algorithms are fast but they tend to be trapped in local minimums, ICA is employed as a global optimum search algorithm to overcome BP neural network adversities, ANN connection weights are formed as variables of ICA and the Mean Square Error is used as a cost function in ICA, composing the new ICA-BP algorithm. Combined with the actual data of wind power plants on the MATLAB platform to validate the method, and a conclusion is made that this algorithm can improve the precision of wind power forecasting.
keywords: imperialist competition algorithm weight value optimization BP nerve network wind power forecast
文章编号：20140302 中图分类号： 文献标志码：
基金项目:国家自然科学基金(60801056);上海市青年科技启明星计划基金(11QA1402800);上海教育委员会科研创新重点项目(11ZZ170)
| 作者 | 单位 | |
| 朱海婷 | 上海电力学院电气工程学院 | zhtl219@126.com |
| 杨宁 | 上海电力学院自动化工程学院 | |
| 王博 | 上海电力学院电气工程学院 |
引用文本：
朱海婷,杨宁,王博.基于人工神经网络的风电功率预测优化算法[J].上海电力大学学报,2014,30(3):203-207,222.
ZHU Haiting,YANG Ning,WANG Bo.Artificial Intelligence Algorithm and Its Optimization in the Wind Power Forecasting Based on Nerve Network[J].Journal of Shanghai University of Electric Power,2014,30(3):203-207,222.
朱海婷,杨宁,王博.基于人工神经网络的风电功率预测优化算法[J].上海电力大学学报,2014,30(3):203-207,222.
ZHU Haiting,YANG Ning,WANG Bo.Artificial Intelligence Algorithm and Its Optimization in the Wind Power Forecasting Based on Nerve Network[J].Journal of Shanghai University of Electric Power,2014,30(3):203-207,222.