Application of Neural Networks for the Prediction of Total Phosphorus Concentrations in Surface Waters
Application of Neural Networks for the Prediction of Total Phosphorus Concentrations in Surface Waters
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DOI：
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发表时间：
2008
影响因子：
1.8
通讯作者：
J. Mozejko;R. Gniot
中科院分区：
文献类型：
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作者：
J. Mozejko;R. Gniot
本文介绍了人工神经网络（ann）在奥德拉河总磷浓度时间序列建模中的应用。来自奥德拉河下游监测站警察的数据被用于培训、验证和测试这些模型。为了证明磷浓度的预测是令人满意的，提出了两个模型：一个是单一输入变量的简单模型，一个是有14个输入变量的复杂模型。两种人工神经网络模型都显示出从新数据集进行预测的高能力。在敏感性分析的基础上，建立了磷浓度与其他水质变量之间的关系。
This paper describes the application of artificial neural networks (ANNs) for the time series modeling of total phosphorous concentrations in the Odra River. Data from the monitoring site Police in the lower part of the Odra were used for training, validating and testing the models. Two models are proposed to prove the satisfactory forecast of phosphorus concentrations: a simpler one with a single input variable and a more complex one with 14 input variables. Both ANN models show a high ability to predict from the new data set. On the basis of sensitivity analysis the relationships between phosphorus concentrations and other water quality variables were established.