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Water quality evaluation of nearshore area using artificial neural network model

机译:人工神经网络在近岸水质评价中的应用

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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:本文在分析历史信息和监测数据的基础上,通过人工神经网络建立了近岸(大连湾)水质评价模型。其中使用反向传播(BP)网络。根据不同时期的水质建立层次预测模型。结果表明,该方法是可行的,可为大连湾水质评价和防治提供科学依据。该方法不需要数据规则,具有客观性,可信性和高度不准确性的特点。同时,预测的相对误差很小。

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