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Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models

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dc.citedby3
dc.contributor.authorMubin Zahari N.en_US
dc.contributor.authorEzzah Shamimi R.en_US
dc.contributor.authorHafiz Zawawi M.en_US
dc.contributor.authorZia Ul-Saufie A.en_US
dc.contributor.authorMohamad D.en_US
dc.contributor.authorid57210914505en_US
dc.contributor.authorid57210920100en_US
dc.contributor.authorid39162217600en_US
dc.contributor.authorid55358162200en_US
dc.contributor.authorid26531534200en_US
dc.date.accessioned2023-05-29T07:24:00Z
dc.date.available2023-05-29T07:24:00Z
dc.date.issued2019
dc.descriptionAir pollution; Errors; Forecasting; Green computing; Mean square error; Ozone; Coefficient of determination; Index of agreements; Linear regression models; Nonlinear regression models; Normalized absolute errors; Performance indicators; Prediction accuracy; Root mean square errors; Linear regressionen_US
dc.description.abstractThe aim of this research is to predict the ozone concentration level for the next three days. Linear regression model and a nonlinear regression model are used to measure the air pollution data and the result was compared. The performance indicator used to evaluate the accuracy of the methods is Index of Agreement (IA), Prediction Accuracy (PA) and Coefficient of Determination (R2). While Normalized Absolute Error (NAE) and Root Mean Square Error (RMSE) are for error measured. The results show that the prediction for the next three days. The highest ozone concentration of the linear regression model is 0.085ppm at Petaling Jaya, Selangor. While the lowest concentration for the linear regression model is 0.015 ppm at Klang, Selangor. Besides, the highest ozone concentration for the nonlinear regression model is 0.1 ppm at Petaling Jaya, Selangor for the second-day prediction. Comparison between the linear regression model and a nonlinear regression model indicates that nonlinear regression model can as an alternative method to the linear regression model. � 2019 Published under licence by IOP Publishing Ltd.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo12006
dc.identifier.doi10.1088/1757-899X/551/1/012006
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85071858594
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85071858594&doi=10.1088%2f1757-899X%2f551%2f1%2f012006&partnerID=40&md5=870fc2b79ac4154ff7f424d8034fd677
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24498
dc.identifier.volume551
dc.publisherInstitute of Physics Publishingen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleIOP Conference Series: Materials Science and Engineering
dc.titlePrediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Modelsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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