| A Method for the Environmental Quality Assessment of Surface Water Based on Artificial Neural Networks |
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| 作者姓名： | YANG Guo\|dong\ \ PAN Da\|feng\ \ FAN Ying\|fang\ .Dep. of Environmental Science Shanxi Uni. Taiyuan China .Shanxi Academy of Agriculture Science Taiyuan China .Institute of Molecular Science Shanxi Uni. Taiyuan C |
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| 作者单位： | YANG Guo\|dong\ 1，\ PAN Da\|feng\ 2，\ FAN Ying\|fang\ 3 1.Dep. of Environmental Science，Shanxi Uni.，Taiyuan 030006，China 2.Shanxi Academy of Agriculture Science，Taiyuan 030031，China 3.Institute of Molecular Science，Shanxi Uni.，Taiyuan 030006，C |
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| 摘 要： | 1 PrefaceArtificial neural networks(ANN) has been becoming a common means used for modelingcomplex″input-output″correlation. Thismodel was also used forforecasting the social andeconomic development and environmental quality comprehensive assessment and so on(WANG Ying etc.,1 997.LIZuo-yong,1 997) .A characteristic of ANN wassimulating acomplex system by means of the interaction strength and the interconnection constructionof the network elements. While the network structure was buil…
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A Method for the Environmental Quality Assessment of Surface Water Based on Artificial Neural Networks |
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| YANG Guo\|dong\ ,\ PAN Da\|feng\ ,\ FAN Ying\|fang\ .Dep. of Environmental Science,Shanxi Uni.,Taiyuan ,China .Shanxi Academy of Agriculture Science,Taiyuan ,China .Institute of Molecular Science,Shanxi Uni.,Taiyuan ,C.A Method for the Environmental Quality Assessment of Surface Water Based on Artificial Neural Networks[J].Journal of Systems Science and Systems Engineering,2000(1). |
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| Authors: | YANG Guo\|dong\ \ PAN Da\|feng\ \ FAN Ying\|fang\ Dep of Environmental Science Shanxi Uni Taiyuan China Shanxi Academy of Agriculture Science Taiyuan China |
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| Institution: | YANG Guo\|dong\ 1,\ PAN Da\|feng\ 2,\ FAN Ying\|fang\ 3 1.Dep. of Environmental Science,Shanxi Uni.,Taiyuan 030006,China 2.Shanxi Academy of Agriculture Science,Taiyuan 030031,China 3.Institute of Molecular Science,Shanxi Uni.,Taiyuan 030006,C |
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| Abstract: | An assessment method for the environmental quality of surface water was established based on artificial neural networks (ANN), in which different classification values were trained as learning samples. The assessment results from the major river section in Datong city indicated that the ANN model have characteristics of simple operation and distinct and quantitative expression of assessment results in comparison with the standard index method for the environmental quality assessment of surface water. |
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| Keywords: | artificial neural newtorks back propagation algorithm surface water quality comprehensive assessment |
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