Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models
Air 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 regression
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Institute of Physics Publishing
2023
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my.uniten.dspace-244982023-05-29T15:24:00Z Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models Mubin Zahari N. Ezzah Shamimi R. Hafiz Zawawi M. Zia Ul-Saufie A. Mohamad D. 57210914505 57210920100 39162217600 55358162200 26531534200 Air 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 regression The 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. Final 2023-05-29T07:24:00Z 2023-05-29T07:24:00Z 2019 Conference Paper 10.1088/1757-899X/551/1/012006 2-s2.0-85071858594 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071858594&doi=10.1088%2f1757-899X%2f551%2f1%2f012006&partnerID=40&md5=870fc2b79ac4154ff7f424d8034fd677 https://irepository.uniten.edu.my/handle/123456789/24498 551 1 12006 All Open Access, Bronze Institute of Physics Publishing Scopus |
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| description |
Air 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 regression |
| author2 |
57210914505 |
| author_facet |
57210914505 Mubin Zahari N. Ezzah Shamimi R. Hafiz Zawawi M. Zia Ul-Saufie A. Mohamad D. |
| format |
Conference Paper |
| author |
Mubin Zahari N. Ezzah Shamimi R. Hafiz Zawawi M. Zia Ul-Saufie A. Mohamad D. |
| spellingShingle |
Mubin Zahari N. Ezzah Shamimi R. Hafiz Zawawi M. Zia Ul-Saufie A. Mohamad D. Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| author_sort |
Mubin Zahari N. |
| title |
Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| title_short |
Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| title_full |
Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| title_fullStr |
Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| title_full_unstemmed |
Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models |
| title_sort |
prediction of future ozone concentration for next three days using linear regression and nonlinear regression models |
| publisher |
Institute of Physics Publishing |
| publishDate |
2023 |
| _version_ |
1806427930804355072 |