Utilising key climate element variability for the prediction of future climate change using a support vector machine model
This paper proposes a support vector machine (SVM) model to advance the prediction accuracy of global land-ocean temperature (GLOT), which is globally significant for understanding the future pattern of climate change. The GLOT dataset was collected from NASA’s GLOT index (C) (anomaly with base:...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Inderscience Enterprises Ltd
2016
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/49995/ http://irep.iium.edu.my/49995/ http://irep.iium.edu.my/49995/ http://irep.iium.edu.my/49995/1/IJGW090201_ABUBAKAR.pdf http://irep.iium.edu.my/49995/4/49995_Utilising%20key%20climate%20element%20variability%20for%20the%20prediction%20of%20future%20climate_Scopus.pdf |
Internet
http://irep.iium.edu.my/49995/http://irep.iium.edu.my/49995/
http://irep.iium.edu.my/49995/
http://irep.iium.edu.my/49995/1/IJGW090201_ABUBAKAR.pdf
http://irep.iium.edu.my/49995/4/49995_Utilising%20key%20climate%20element%20variability%20for%20the%20prediction%20of%20future%20climate_Scopus.pdf