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Simulation of the concentration of dissolved oxygen in river waters using Artificial Neural Networks

机译:人工神经网络模拟河水中溶解氧的浓度

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The present study was to develop a model on Artificial Neural Networks (ANN) in order to estimate the oxygen dissolved in the water of the river Alegria, located in Medianeira in the state of Paran. The model was developed based on data from the river water quality over the study interval. For training and validation of the model were generated 132 data groups: with 22 collections in 6 seasons. The input variables in the network were the water quality parameters except the (OD), which set as output. Given the results of the simulations carried out in order to predict the concentration of oxygen dissolved in the river water, depending on the number of variables involved, with an average error of 11, 42% can be concluded that a neural network can be used to predict the available oxygen in the waters of a river.
机译:本研究旨在开发一种人工神经网络(ANN)模型,以估算位于Paran州Medianeira的Alegria河水中的溶解氧。该模型是根据研究间隔期间河流水质的数据开发的。为了训练和验证模型,生成了132个数据组:6个季节中有22个集合。网络中的输入变量是除(OD)外的水质参数,将其设置为输出。给定进行的模拟结果以预测溶解在河水中的氧气浓度,具体取决于所涉及的变量数量,平均误差为11,可以得出42%的结论是,可以使用神经网络来预测河流水域中的可用氧气。

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