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Proceedings Paper

Prediction models for CO2 emission in Malaysia using best subsets regression and multi-linear regression
Author(s): C. H. Tan; M. Z. Matjafri; H. S. Lim
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Paper Abstract

This paper presents the prediction models which analyze and compute the CO2 emission in Malaysia. Each prediction model for CO2 emission will be analyzed based on three main groups which is transportation, electricity and heat production as well as residential buildings and commercial and public services. The prediction models were generated using data obtained from World Bank Open Data. Best subset method will be used to remove irrelevant data and followed by multi linear regression to produce the prediction models. From the results, high R-square (prediction) value was obtained and this implies that the models are reliable to predict the CO2 emission by using specific data. In addition, the CO2 emissions from these three groups are forecasted using trend analysis plots for observation purpose.

Paper Details

Date Published: 14 October 2015
PDF: 7 pages
Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015, 963812 (14 October 2015); doi: 10.1117/12.2195442
Show Author Affiliations
C. H. Tan, Univ. Sains Malaysia (Malaysia)
M. Z. Matjafri, Univ. Sains Malaysia (Malaysia)
H. S. Lim, Univ. Sains Malaysia (Malaysia)

Published in SPIE Proceedings Vol. 9638:
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
Charles R. Bostater; Stelios P. Mertikas; Xavier Neyt, Editor(s)

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