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Modelling nitrate pollution of groundwater using artificial neural network and genetic algorithm in an arid zone

机译:人工神经网络和遗传算法在干旱区地下水硝酸盐污染模拟中的应用。

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摘要

This paper presents a hybrid approach to analyse nitrate pollution based on an Artificial Neural Network (ANN) and Genetic Algorithm (GA). This makes it possible to compute the amount of nitrate in different time-scales easily without employment of confusing complicated mathematical equations. Generally, the results of the current research could be useful in management purposes and also for beneficiaries of groundwater. Isfahan province, located in a dry region of Iran, was chosen as the study area.
机译:本文提出了一种基于人工神经网络(ANN)和遗传算法(GA)的混合方法来分析硝酸盐污染。这使得可以轻松计算不同时间范围内的硝酸盐含量,而无需使用复杂的数学方程式。通常,当前研究的结果可能对管理目的以及对地下水的受益者有用。位于伊朗干旱地区的伊斯法罕省被选为研究区域。

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