Air Quality Index and Air Pollutant Concentration Prediction Based on Machine Learning Algorithms
نویسندگان
چکیده
منابع مشابه
Machine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
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† Dalhousie University, Halifax NS, Canada. B3H 3J5 § Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA 02138 ±Universities Space Research Association, Columbia, MD 21044, USA ÐAtmospheric Chemistry and Dynamics Laboratory, Earth Sciences Division, NASA Goddard Space Flight Center, MD 20771, USA ¥University of British Columbia, Vancouver, BC, Canada. V6T 1Z3 ‡ Air Quality Processe...
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There are many substances in the air which may impair the health of plants and animals, including humans, that arise both from natural processes and human activity. Nitrogen dioxide NO2 and particulate matter (PM10, PM2.5) emissions constitute a major concern in urban areas pollution. The state of the air is, in fact, an important factor in the quality of life in the cities, since it affects th...
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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 local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentrati...
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ژورنال
عنوان ژورنال: Applied Sciences
سال: 2019
ISSN: 2076-3417
DOI: 10.3390/app9194069