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Water quality evaluation of nearshore area using artificial neural network model

机译:利用人工神经网络模型对近岸区域的水质评价

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In this paper, a water quality evaluation model of nearshore (Dalian Bay) is built through artificial neural network based on the analysis of history information and monitoring data. In which a back propagation (BP) network is used. A hierarchical prediction model is established according to water quality at different period. Results illustrates the methodology is practicable and can be provided scientific proof for water quality evaluation and prevention of Dalian Bay.The method does not demand data's rules and has the characteristic of impersonality, credibility and highly inaccuracy permission. At the same time the predictive relative error is little.
机译:本文基于历史信息分析和监测数据,通过人工神经网络建立了近岸(大连湾)的水质评估模型。其中使用反向传播(BP)网络。根据不同时期的水质建立分层预测模型。结果说明了该方法可行的方法,可以提供大连海湾水质评估和预防的科学证据。该方法不要求数据的规则,具有模拟,可信度和高度不准确许可的特征。同时预测相对误差很少。

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