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基于ARIMA算法和小波分析+BP神经网络算法的短期负荷预测

上传者: yemaoxingtianxia1 | 上传时间:2024/7/16 11:31:37 | 文件大小:8.95MB | 文件类型:rar
基于ARIMA算法和小波分析+BP神经网络算法的短期负荷预测
我们用了两种算法对PJM某区电力负荷进行超短期预测。
ARIMA算法预测速度较快,平均误差在3%以内,特别适合这种超短期负荷预测,而小波分析+BP神经网络算法是一种适应性比较广的算法,在此次超短期负荷预测中它的平均误差在7%以内,预测时间相对更长。
此程序由华北电力大学电力专业学生编写,采用了VB、MATLAB混合编程(VB的界面,MATLAB的内核),利用了2种算法实现电力负荷超短期预测,这2种方法都是当前较先进实用的算法,十分有启发性。
本软件ID:4947372

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评论信息

  • blpdqmocyw:
    学习,可以参考学习2017-12-23
  • stevenge:
    貌似没有考虑数据的趋势项,没有做差分去信号的非平稳性2017-12-02
  • qq_23106463:
    不值这么多积分2017-03-22
  • z1zhangyanan:
    这个方法正好是我看到一个文章里边的研究,这样可以拿来验证一下,方便研究!2015-09-10
  • MultiKKray:
    程序较老,各种报错。2015-03-25

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