Prediction of Future Ozone Concentration for Next Three Days Using Linear Regression and Nonlinear Regression Models
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 Ind...
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my.uniten.dspace-128852020-07-07T04:57:50Z 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. 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. 2020-02-03T03:27:34Z 2020-02-03T03:27:34Z 2019 Conference Paper 10.1088/1757-899X/551/1/012006 en |
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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. |
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_facet |
Mubin Zahari, N. Ezzah Shamimi, R. Hafiz Zawawi, M. Zia Ul-Saufie, A. Mohamad, D. |
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 |
publishDate |
2020 |
_version_ |
1672614186536927232 |
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13.222552 |