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改进型灰色神经网络模型在水质预测中的应用
引用本文:胡玉琢,张云怀,肖鹏,曹六俊,卢露,张小宁.改进型灰色神经网络模型在水质预测中的应用[J].黑龙江大学自然科学学报,2009,26(5).
作者姓名:胡玉琢  张云怀  肖鹏  曹六俊  卢露  张小宁
作者单位:重庆大学化学化工学院,重庆,400044
基金项目:重庆大学研究生科技创新基金项目(200904A1A0010310)
摘    要:介绍了三类改进的灰色模型和BP神经网络。将三类改进的灰色模型与神经网络进行组合,得到改进型灰色神经网络组合模型,将一维序列通过三个改进的灰色模型得到三组值作为神经网络的输入,原始序列作为神经网络的输出,训练得到最佳神经网络结构。将组合模型应用到嘉陵江磁器口断面总磷浓度的预测中,结果表明:(1)用该组合模型进行预测,相对误差均在5%以下,预测精度较高,取得了较理想的预测效果;(2)WPGM(1,1)、pGM(1,1)、CGM(1,1)、组合模型预测的平均相对误差分别为5.05%、34.01%、33.65%、3.02%,与单一灰色预测方法和灰色神经网络模型相比,组合模型的适应能力和预测推广能力更好,预测精度更高。

关 键 词:灰色预测  神经网络  水质预测  嘉陵江  

Application of improved grey neural network model to water quality prediction
HU Yu-zhuo,ZHANG Yun-huai,XIAO Peng,CAO Liu-jun,LU Lu,ZHANG Xiao-ning.Application of improved grey neural network model to water quality prediction[J].Journal of Natural Science of Heilongjiang University,2009,26(5).
Authors:HU Yu-zhuo  ZHANG Yun-huai  XIAO Peng  CAO Liu-jun  LU Lu  ZHANG Xiao-ning
Institution:College of Chemistry and Chemical Engineering;Chongqing University;Chongqing 400044;China
Abstract:The three types of improved grey model and BP artificial neural network are introduced.Improved grey neural network combined model was combined three categories of improved grey model and neural network.Then got three sets of number which is made use of three improved grey prediction models with one-dimensional sequence as the neural network's inputs,and the original sequence was used as the output of the neural network.The neural network was trained to get the optimal structure.The combined model was appli...
Keywords:grey prediction  neural network  water quality prediction  Jialing river  
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