A hybrid approach to modelling the climate change effects on Malaysia’s oil palm yield at the regional scale

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Date
2014-06-16
Authors
Shanmuganathan, S
Narayanan, A
Mohamed, M
Ibrahim, R
Haron, K
Supervisor
Item type
Conference Contribution
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Soft Computing and Data Mining (SCDM), University Tun Hussein Onn, Malaysia
Abstract

Understanding the climate change effects on local crops is vital for adapting new cultivation practices and assuring world food security. Given the volume of palm oil produced in Malaysia, climate change effects on oil palm phenology and fruit production have greater implications at both local and international scenes. In this context, the paper looks at analysing the recent climate change effects on oil palm yield within a five year period (2007-2011) at the regional scale. The hybrid approach of data mining techniques (association rules) and statistical analyses (regression) used in this research reveal new insights on the effects of climate change on oil palm yield within this small data set insufficient for conventional analyses on their own

Description
Keywords
Regression test , Data mining (association rules) , WEKA , JRip
Source
The First International Conference on Soft Computing and Data Mining (SCDM 2014) held at Universiti Tun Hussein Onn Malaysia (UTHM), Johor, Malaysia, 2014-06-16to 2014-06-18
DOI
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NOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version).