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基于非等时距加权灰色模型与神经网络的组合预测算法

韩晋 杨岳 陈峰 李雄兵

韩晋, 杨岳, 陈峰, 李雄兵. 基于非等时距加权灰色模型与神经网络的组合预测算法[J]. 应用数学和力学, 2013, 34(4): 408-419. doi: 10.3879/j.issn.1000-0887.2013.04.009
引用本文: 韩晋, 杨岳, 陈峰, 李雄兵. 基于非等时距加权灰色模型与神经网络的组合预测算法[J]. 应用数学和力学, 2013, 34(4): 408-419. doi: 10.3879/j.issn.1000-0887.2013.04.009
HAN Jin, YANG Yue, CHEN Feng, LI Xiong-bin. Combination Forecasting Algorithm Based on Non-Equal Interval Weighted Grey Model and Neural Network[J]. Applied Mathematics and Mechanics, 2013, 34(4): 408-419. doi: 10.3879/j.issn.1000-0887.2013.04.009
Citation: HAN Jin, YANG Yue, CHEN Feng, LI Xiong-bin. Combination Forecasting Algorithm Based on Non-Equal Interval Weighted Grey Model and Neural Network[J]. Applied Mathematics and Mechanics, 2013, 34(4): 408-419. doi: 10.3879/j.issn.1000-0887.2013.04.009

基于非等时距加权灰色模型与神经网络的组合预测算法

doi: 10.3879/j.issn.1000-0887.2013.04.009
基金项目: 国家自然科学基金资助项目(51005252)
详细信息
    作者简介:

    韩晋(1990—),男,安徽人,硕士生(E-mail:silmarhan@gmail.com);杨岳(1962—),男,湖南人,教授,博士生导师(通讯作者. E-mail:yangyueteacher@163.com) .

  • 中图分类号: O241

Combination Forecasting Algorithm Based on Non-Equal Interval Weighted Grey Model and Neural Network

  • 摘要: 非等时距预测算法在不等时间间隔序列的趋势分析与预测方面具有重要作用.在传统灰色预测理论的基础上,提出一种基于非等时距加权灰色模型和神经网络的组合预测算法.通过构建非等时距加权灰色预测模型,将原始数据序列的平均值作为累加序列初值,将连续累积函数的积分面积作为背景值,对累加序列进行加权处理,以真实反映时间序列发展对预测结果的影响.在此基础上,引入BP神经网络对灰色预测的残差序列进行修正,进一步提高了预测精度.经算例验证,该算法预测精度达到1级,且高于类似算法.
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出版历程
  • 收稿日期:  2013-02-08
  • 修回日期:  2013-03-25
  • 刊出日期:  2013-04-15

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