Predicting particulate matter (PM2.5) in Malaysia using Multiple Linear Regression and Artificial Neural Network

Predicting particulate matter (PM2.5) in Malaysia using Multiple Linear Regression and Artificial Neural Network

Air pollution is a well-known issue for all countries, including Malaysia. It has been stated that particulate matter that less than 2.5mm known as PM2.5 has a greater effect on health as the smaller particulate size can penetrate deep into the respiratory system and affect the cardiovascular system...

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Bibliographic Details
Main Authors: Baser, N.A (Author), Ismail, N.A (Author), Malik, M.A.A (Author), Rahman, R.A (Author), Sobri, N.M (Author), Sukhairi, S.A.M (Author), Wan Yaacob, W.F (Author), Yaacob W.F.W (Author)
Format: Article
Language:English
Published: IOP Publishing Ltd 2021
Subjects:
Air quality
Artificial neural network
Carbon monoxide
Cardiovascular system
Descriptive analysis
Forecasting
Indicator parameters
Malaysia
Mean square error
Multiple linear regression
Multiple linear regressions
Neural networks
Nitrogen oxides
Particles (particulate matter)
Particulate Matter
Particulate size
Particulate size (pm2.5)
Particulate size (PM2.5)
PM2.5 concentration
Respiratory system
Sulfur dioxide
Trend analysis
Wind
Wind speed
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