首页> 外文会议>2011 IEEE International Conference on Computer Science and Automation Engineering >Short-term power system load forecasting based on improved BP artificial neural network
【24h】

Short-term power system load forecasting based on improved BP artificial neural network

机译:基于改进BP神经网络的短期电力系统负荷预测

获取原文

摘要

The accuracy of the forecast of power system loan, which is an important part of the forecast of short-term power system loan, will directly affect the economic of the power systems and its security and stability. The use of artificial neural network could get the similar feature like nonlinear system and use it on the short-term forecast. Researches about adding momentum into the improved BP network and combinating the same type of vague and mapping results when building input networks shows that it has better performance than standard BP algorithms. Meanwhile, after classification the input data categorize and dealing with the linear activate, putting these data to the corresponding sets, the result proved that its accuracy is higher than the standard of artificial neural network.
机译:电力系统贷款预测的准确性是短期系统贷款预测的重要组成部分,将直接影响电力系统的经济性及其安全性和稳定性。人工神经网络的使用可以得到类似非线性系统的特征,并将其用于短期预测。关于在构建输入网络时向改进的BP网络中添加动量并组合相同类型的模糊和映射结果的研究表明,该方法具有比标准BP算法更好的性能。同时,对输入数据进行分类和线性激活处理后,将这些数据放入相应的集合中,结果证明其准确性高于人工神经网络的标准。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号