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灰色技术与小波网络融合的多因素预测模型
引用本文:严磊,钟波,罗会亮,雷邦军.灰色技术与小波网络融合的多因素预测模型[J].山西师范大学学报,2010(4).
作者姓名:严磊  钟波  罗会亮  雷邦军
作者单位:重庆大学数理学院;黔南民族师范学院数学系;贵阳学院数学系;
基金项目:贵州省自然科学基金项目(黔科教20090045)
摘    要:针对多因素预测中预测对象与影响因素之间具有非线性相关性、预测对象及其影响因素呈随机性、非线性变化的特点,同时各影响因素对预测对象的重要程度不尽相同,学习样本容量小、信息不充分,充分利用小波神经网络对非线性函数的强大拟合能力和灰色累加技术弱化原始数据随机性、增强规律性的优势,建立了灰色小波神经网络融合的多因素预测模型,并将其应用于交通量预测中.结果表明,与BP网络比较,所建模型可行有效,且提高了预测精度.

关 键 词:灰色技术  小波神经网络  预测  

Multi-factor Forecasting Model on the Integration of Grey Technology and Wavelet Network
YAN Lei,ZHONG Bo,LUO Hui-liang,LEI Bang-jun.Multi-factor Forecasting Model on the Integration of Grey Technology and Wavelet Network[J].Journal of Shanxi Teachers University,2010(4).
Authors:YAN Lei  ZHONG Bo  LUO Hui-liang  LEI Bang-jun
Institution:YAN Lei1,ZHONG Bo1,LUO Hui-liang2,LEI Bang-jun3(1.College of Mathematics and Physics,Chongqing University,Chongqing 400044,China,2.Deptartment of Mathematics,Qiannan Normal College of Nationalities,Duyun 558000,Guizhou,3.Deptartment of Mathematics,Guiyang Universty,Guiyang 550003,China)
Abstract:In the multi-factor forecasting work,the forecasting objects and their influencing factors usually bear the non-linear relativity and have the characteristics of randomicity and non-linear movement,and at the same time the importance degree of each factor to the forecasting objects are not exactly the same,and also the capacity of study samples are small and information is insufficient.The multifactor foresting model which is the amalgamation of the grey wavelet neural network is established and applied to ...
Keywords:grey technology  wavelet neural network  forecasting  
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