| 基于RBF神经网络的湖库水质富营养化程度评价模型 |
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| 引用本文： | 张晓丹,黄朝君,徐菡,刘钦圣.基于RBF神经网络的湖库水质富营养化程度评价模型[J].环境工程,2007,25(2):80-82. |
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| 作者姓名： | 张晓丹 黄朝君 徐菡 刘钦圣 |
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| 作者单位： | 北京科技大学应用科学学院,北京,100083 |
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| 摘 要： | 运用人工神经网络中的RBF网络算法,建立一种新的湖库水质富营养化程度评价模型。对我国污染差异分布广泛的12个湖库的水质富营养程度评价数据中的10组作为训练样本进行网络的建立,剩余2组用于网络的检验。结果表明:该方法建立的评价模型比文献1]利用多元统计分析方法建立的评价模型更加简便有效。
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| 关 键 词： | 富营养化 RBF网络 人工神经网络 |
| 修稿时间： | 2006-09-05 |
MODEL OF ASSESSING LAKE AND RESERVOIR EUTROPHICATION BASED ON RBF NETWORK |
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| Zhang Xiaodan Huang Zhaojun Xu Han et al.MODEL OF ASSESSING LAKE AND RESERVOIR EUTROPHICATION BASED ON RBF NETWORK[J].Environmental Engineering,2007,25(2):80-82. |
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| Authors: | Zhang Xiaodan Huang Zhaojun Xu Han |
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| Institution: | Zhang Xiaodan Huang Zhaojun Xu Han et al |
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| Abstract: | A new model of lake and reservoir eutrophication assessment can be established with RBF network of artificial neural network.There are twelve groups of given data,of which ten groups are used to establish network and two groups are used to test the network.The results show that the RBF network is better than the methods of principal component analysis and discriminant analysis in solving the problems of water eutrophication assessment. |
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| Keywords: | ertrophication RBF network and artificial neural network |
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