AIMC Topic: Air Pollution

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Using machine learning to identify air pollution exposure profiles associated with early cognitive skills among U.S. children.

Environmental pollution (Barking, Essex : 1987)
Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air ...

Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang.

PloS one
Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it i...

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model.

International journal of environmental research and public health
The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies ...

Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong.

International journal of environmental research and public health
With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some lo...

Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining.

Artificial intelligence in medicine
OBJECTIVES: Traditional studies on effects of outdoor pollution on asthma have been criticized for questionable statistical validity and inefficacy in exploring the effects of multiple air pollutants, alone and in combination. Association rule mining...

Deep learning architecture for air quality predictions.

Environmental science and pollution research international
With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and...

Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

PloS one
Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services f...

Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks.

Environmental science and pollution research international
In this paper, we predict air pollutant concentration using a feedforward artificial neural network inspired by the mechanism of the human brain as a useful alternative to traditional statistical modeling techniques. The neural network is trained bas...

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

Computational intelligence and neuroscience
The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parame...