Air quality prediction using artificial neural network
Over the last few years, the use of artificial neural networks (ANNs) has increased in many areas of engineering. Artificial neural network have been applied to many environmental engineering problems and have demonstrated some degree of success. The aim of study is to develop neural network air qua...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
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| Online Access: | http://eprints.uthm.edu.my/2528/ http://eprints.uthm.edu.my/2528/1/Air_Quality_Prediction_Using_Artificial_Neural_Network.pdf |
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| Summary: | Over the last few years, the use of artificial neural networks (ANNs) has increased in many
areas of engineering. Artificial neural network have been applied to many environmental
engineering problems and have demonstrated some degree of success. The aim of study is to
develop neural network air quality prediction model. In this study, a prediction method is
developed using feed-forward neural network. Several parameters such as sulphur dioxide
(SO2), carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NO), temperature,
relative humidity and air velocity are considered in this study. The performance of the
developed model was assessed through a measure of Mean Square Error (MSE) and value of
R2. From the constructed networks, the best prediction performance was observed in a model
with network structure 7-20-4 with R2 value of 0.57 and MSE 0.062. |
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