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Air Quality Prediction in Yinchuan by Using Neural Networks

机译:基于神经网络的银川市空气质量预测

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A field study was carried out in Yinchuan to gather and evaluate information about the real environment. Oy (Ozone), PMw (particle 10 um in diameter and smaller) and SO2 (sulphur monoxide) constitute the major concern for air quality of Yinchuan. This paper addresses the problem of the predictions of such three pollutants by using the ANN. Because ANNs are non-linear mapping structure based on the function of the human brain. They have been shown to be universal and highly flexible function approximation for any date. These make powerful tools for models, especially when the underlying data relationship is unknown.
机译:在银川进行了实地研究,以收集和评估有关真实环境的信息。 Oy(臭氧),PMw(直径10微米或更小的颗粒)和SO2(一氧化硫)是影响银川空气质量的主要因素。本文使用人工神经网络解决了对这三种污染物的预测问题。因为人工神经网络是基于人脑功能的非线性映射结构。已经证明它们在任何日期都是通用且高度灵活的函数近似值。这些工具为模型提供了强大的工具,尤其是在基础数据关系未知的情况下。

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