基于相空间重构的神经网络短期风速预测

被引:20
作者
廖志强 [1 ]
李太福 [2 ]
余德均 [3 ]
程杨 [4 ]
姚立忠 [1 ]
机构
[1] 西安石油大学电子工程学院
[2] 重庆科技学院电气与信息学院
[3] 重庆电力高等专科学校实践教学部
[4] 重庆市农业科学院
关键词
相空间重构; 互信息法; 虚假最近邻点法; BP神经网络; 风速预测;
D O I
暂无
中图分类号
P183 [地球]; P425 [风];
学科分类号
摘要
针对风速具有较强的混沌特性,预测难度较大,提出了一种基于相空间重构的神经网络短期风速预测方法:对数据进行小波降噪,运用互信息法和虚假最近邻点法确定最佳的延迟时间和嵌入维数,对样本空间进行重构,使新的样本能够表征原始时间序列动态特性,更能反映风速变化特性。在此基础上运用BP神经网络进行短期风速预测。实验结果表明短期风速预测精度得到提高。
引用
收藏
页码:14 / 18
页数:5
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