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Modelling of urban air pollution in the Edmonton Strathconoa Industrial Area using artificial neural networks.

机译：使用人工神经网络对埃德蒙顿Strathconoa工业区的城市空气污染进行建模。

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Exposure to air pollution has become an exceedingly inescapable part of urban living. An important facet of the control and abatement of urban air pollution (UAP) is the use of modelling. Current modelling techniques generally use mathematics to describe transport and dispersion mechanisms of pollutants, and predict their levels at given locations away from a source. However, due to mathematical constraints, these models have limited success in dealing with complex airsheds containing many point and non-point sources of UAP.;Artificial Neural Network (ANN) modelling is a technique that effectively models non-linear type processes, such as those governing complex urban air pollution situations. The objective of this study was to investigate the use of ANN to model UAP, namely oxides of nitrogen, in the Strathcona Industrial Area, east of the City of Edmonton. This study found that ANN is a promising and effective technique for modelling hourly oxide of nitrogen fluctuations in an urban environment.

机译：暴露在空气污染中已经成为城市生活中一个不可回避的部分。控制和消除城市空气污染（UAP）的一个重要方面是建模的使用。当前的建模技术通常使用数学来描述污染物的迁移和扩散机制，并预测远离源的给定位置的污染物水平。但是，由于数学上的限制，这些模型在处理包含许多UAP点和非点源的复杂空域方面取得的成功有限。;人工神经网络（ANN）建模是一种有效地对非线性类型过程进行建模的技术，例如那些管理复杂的城市空气污染状况的机构。这项研究的目的是研究埃德蒙顿市以东的Strathcona工业区中ANN模型对UAP的建模，即氮的氧化物。这项研究发现，人工神经网络是一种有前途且有效的技术，可用于模拟城市环境中每小时的氮波动的氧化物。

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作者
Hasham, Faizal Ali.;
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作者单位

University of Alberta (Canada).;

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授予单位 University of Alberta (Canada).;
学科 Engineering Environmental.;Physics Atmospheric Science.;Artificial Intelligence.;Geography.
学位 M.Sc.
年度 1998
页码 137 p.
总页数 137
原文格式 PDF
正文语种 eng
中图分类老年病学;
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机译：通过人工神经网络，回归和敏感性模型的比较分析，对臭氧空气污染的展望通过人工神经网络，回归和敏感性模型的比较分析，对臭氧空气污染的展望。
2. Models of self-organizing artificial neural networks to identify stationary industrial sources of air pollution [J] . S. P. Dudarov Mathematical models and computer simulations . 2017,第4期

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3. Spatial estimation of urban air pollution with the use of artificial neural network models [J] . A. Alimissis, K. Philippopoulos, C.G. Tzanis, Atmospheric environment . 2018,第OCTa期

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4. Artificial Neural Network Modeling and Forecasting ofHourly PM2.5 in urban air in Edmonton [C] . Mohamed Gamal El-Din, Madhan Selvaraj, Ahmed G. El-Din, Air & Waste Management Association's annual conference & exhibition;A&WMA's annual conference & exhibition . 2005

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Modelling of urban air pollution in the Edmonton Strathconoa Industrial Area using artificial neural networks.

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