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Application of artificial neural network on water quality evaluation of Fuyang River in Handan city

机译:人工神经网络在邯郸市阜阳河水质评价中的应用

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To accurately reflect the water quality of Fuyang River in Handan city, monitoring sampling and laboratory analysis of water quality were conducted, and two kinds of water quality evaluation models, the BP neural network model and the RBF neural network model, were constructed on the basis of artificial intelligence and neural network theories. Partial water quality data of surface water environmental quality standard were chosen as training samples, and the water quality monitoring data were chosen as input samples, these two water quality evaluation models were applied to assess the comprehensive water quality of Fuyang River in Handan city, the evaluation results show that the water quality grade of Fuyang River is III. And these two models are simple and convenient in application and have better practicability. And it can be seen that RBF neural network is superior to BP neural network in the network training process.
机译:为准确反映邯郸市阜阳河水质,进行了水质监测取样和实验室分析,在此基础上构建了BP神经网络模型和RBF神经网络模型两种水质评价模型。人工智能和神经网络理论选择地表水环境质量标准的部分水质数据作为训练样本,选择水质监测数据作为输入样本,运用这两个水质评价模型对邯郸市阜阳河综合水质进行评价。评价结果表明,富阳河水质等级为Ⅲ级。并且这两种模型使用简单方便,具有较好的实用性。可以看出,在网络训练过程中,RBF神经网络优于BP神经网络。

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