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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Prediction and Analysis of Pollution Levels in Delhi Using Multilayer Perceptron
verfasst von : Aly Akhtar, Sarfaraz Masood, Chaitanya Gupta, Adil Masood
Erschienen in: Data Engineering and Intelligent Computing
Verlag: Springer Singapore
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Abstract
Air Pollution is a major problem faced by humans worldwide and is placed in the top ten health risks. Particulate Matter (PM10) is one of the major parameters to measure the air quality of an area. These are the particulate matter of the size 10 μm or less suspended in the air. PM10 occur naturally from volcanoes, forest fire, dust storms etc., as well as from human activities like coal combustion, burning of fossil fuels etc. The PM10 value is predicted by multilayer perceptron algorithm, which is an artificial neural network, Naive Bayes algorithm and Support Vector Machine algorithm. Total of 9 meteorological factors are considered in constructing the prediction model like Temperature, Wind Speed, Wind Direction, Humidity etc. We have then constructed an analysis model to find the correlation between the different meteorological factors and the PM10 value. Results are then compared for different algorithms, which show MLP as the best.