Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Mathivanan Mathivanan
Universiti Tenaga Nasional

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Ozone prediction based on support vector machine M. Tanaskuli; Ali N. Ahmed; Nuratiah Zaini; Samsuri Abdullah; Abdoulhdi A. Borhana; N. A. Mardhiah; Mathivanan Mathivanan
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1461-1466

Abstract

The prediction of tropospheric ozone concentrations is very important due to negative effects of ozone on human health, atmosphere and vegetation. Ozone Prediction is an intricate procedure and most of the conventional models cannot provide accurate prediction. Machine Learning techniques have been widely used as an effective tool for prediction. This study is investigating the implementation of Support vector Machine-SVM to predict Ozone concentrations. The results show that the SVM is capable in predicting ozone concentrations with acceptable level of accuracy. Sensitivity analysis has been conducted to show what is the most effective parameters on the proposed model.
Co-Authors Abdoulhdi A. Borhana Ali N. Ahmed M. Tanaskuli N. A. Mardhiah Nuratiah Zaini Samsuri Abdullah