Author:
Mamat Mazlina,Mustakim Rosminah,Johari Nadhirah
Publisher
Springer Nature Singapore
Reference15 articles.
1. Azid, A., Juahir, H., Toriman, M.E., Kamarudin, M.K.A., Yamin, M.: Prediction of the level of air pollution using principal component analysis and artificial neural network techniques: A case study in Malaysia. Water, Air, Soil Pollut. 225(8) (2014)
2. Afzali, A., Rashid, M., Afzali, M., Younesi, V.: Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model. J. Clean. Prod. 166, 1216–1225 (2017)
3. Fong, S.Y., Abdullah, S., Ismail, M.: Forecasting of particulate matter (PM10) concentration based on gaseous pollutants and meteorological factors for different monsoons of urban coastal area in Terengganu. J. Sustain. Sci. Manag. 5, 3–17 (2018)
4. Leong, W.C., Kelani, R.O., Ahmad, Z.: Prediction of air pollution index (API) using support vector machine (SVM). J. Environ. Chem. Eng. 8(3) (2020)
5. Koo, J.W., Wong, S.W., Selvachandran, G., Long, H.V., Son, L.H.: Prediction of air pollution index in Kuala Lumpur using fuzzy time series and statistical models. Air Qual. Atmos. Health 13(1), 77–88 (2020)