Title: Discovering meaningful patterns for tropical climate change in Malaysia
Authors: Ghassan Saleh Al-Dharhani; Zulaiha Ali Othman; Azuraliza Abu Bakar; Sharifah Mastura Syed Abdullah
Addresses: Data Mining and Optimization Group, Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Malaysia ' Data Mining and Optimization Group, Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Malaysia ' Data Mining and Optimization Group, Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Malaysia ' Institute of Climate Change, Universiti Kebangsaan Malaysia, Malaysia
Abstract: This paper investigated patterns of climate change in Malaysia and proposed a fuzzy based symbolic data representation known as a shapelet patterns algorithm (SPA). The Shapelet Pattern visualise climate change patterns in the form of coloured shapes to indicate annual changes in temperature patterns. The experiment used climate change data collected from four stations in Malaysia, Petaling-jaya, Subang, KLIA-Sepang and University Malaya, to produce three types of results. The results revealed various climate change patterns that can be used by climate change experts to further analyse the effects of climate change and for better decision making.
Keywords: time series; symbolic data representation; climate shapelet patterns; fuzzy logic; climate change; Malaysia.
International Journal of Global Warming, 2018 Vol.15 No.2, pp.157 - 174
Received: 25 Apr 2016
Accepted: 06 Mar 2017
Published online: 02 Jul 2018 *