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有机灰色神经网络模型在河流水质预测中的应用
引用本文:朱长军,史红亮,周继红,张普,赵秀娟.有机灰色神经网络模型在河流水质预测中的应用[J].三峡大学学报(自然科学版),2007,29(3):193-196.
作者姓名:朱长军  史红亮  周继红  张普  赵秀娟
作者单位:1. 河海大学,水资源环境学院,南京,210098;河北工程大学,城市建设学院,河北,邯郸,056038
2. 淮河水利水电开发总公司,安徽,蚌埠,233001
3. 河海大学,水资源环境学院,南京,210098
摘    要:针对灰色预测对波动较强的序列只能预测大致变化的缺陷,在分析河流水质动态变化的基础上,结合灰色理论中的GM(1,1),无偏GM(1,1)和RBF神经网络的特点,提出有机灰色神经网络预测模型,将灰色模型得到的数值作为神经网络的输入,原始数据作为神经网络的输出,训练得到最佳神经网络结构.以某地区河流水质为例,根据其变化规律,应用有机灰色神经网络模型进行预测,结果表明,该模型拟合误差小,预测精度高.

关 键 词:灰色预测  有机灰色神经网络  河流水质  RBF神经网络
文章编号:1672-948X(2007)03-0193-04
修稿时间:2007-03-30

Application of Organic Gray Neural Network Model to River Water Quality Prediction
Zhu Changjun,Shi Hongliang,Zhou Jihong,Zhang Pu,Zhao Xiujuan.Application of Organic Gray Neural Network Model to River Water Quality Prediction[J].Journal of China Three Gorges University(Natural Sciences),2007,29(3):193-196.
Authors:Zhu Changjun  Shi Hongliang  Zhou Jihong  Zhang Pu  Zhao Xiujuan
Institution:1. College of Water Resources and Environment, Hohai Univ. , Nanjing 210098, Chinas2. College of Urban Construction, Hebei Univ. of Engineering, Handan 056038, China;3. Huaihe Conservancy and Hydropower Development Company, Bengbu,233001, China
Abstract:In view of the defect that the gray method can only predict the tendency approximately,a new organic gray neural network model is proposed by the advantages of GM(1,1),gray residual difference identification and RBF neural network,based on the analysis of the river water quality.The three groups data got from the gray model is used as the input of the neural network and the origin data are used as the output of neural network.The neural network is trained to get the optimal structure of neural network.According to the dynamic law of a certain river water quality in some region,the water quality is predicted by using organic gray neural network model.The results show that the model has highly fitting and predicting precision advantages than other model.
Keywords:gray prediction  organic neural network  river water quality  RBF neural network
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