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The prediction of comprehensive pollution indexes of Taihu Lake based on BP network

机译:基于BP网络的太湖综合污染指数预测

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In order to provide decision support for management platform of Taihu Lake,this paper studied BP(Back Propagation) neural network model and used it into predicting of the comprehensive pollution index of inter rivers and out rivers of Taihu Lake.This paper established a three-layer BP neural network prediction model,based on Taihu routine environmental monitoring data,predicted the quality of water,studied the relationship between the variation of water quality of Taihu and inflow and outflow rivers of Taihu.The prediction of 2005 year Taihu's water quality showed that,in 2005 the water quality pollution is more seriously than before,generally V water quality.The result is in line with the pollution situation development trend of Taihu Lake.The reason why BP neural network was selected are as follows.Compared with the former methods,BP network method have good adaptability,higher precision,better response indexes of water indexes' internal change rules.What this paper studied can provide scientific basis for limiting water environmental pollution.
机译:为了为太湖湖的管理平台提供决策支持,本文研究了BP(背部传播)神经网络模型,并用它来预测太湖河流河流河流综合污染指数。本文建立了三个 - 基于太湖常规环境监测数据的层BP神经网络预测模型预测了水的质量,研究了太湖水质变化与太湖流量河流的关系。2005年的太湖水质的预测显示,2005年水质污染比以前更严重,一般为水质。结果符合太湖湖的污染情况发展趋势。选择了BP神经网络的原因如下。 ,BP网络方法具有良好的适应性,更高的精度,更好的水指数的响应指标的内部变化规则。本文研究了如何散发解放水环境污染的科学基础。

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