FUZZY AUTOCATALYTIC SET FOR ANALYSIS OF CLIMATE PATTERNS AND THEIR REGIONAL VARIABILITY
Abstract
Over the past few decades, climate change and global warming have become serious global issues. In Malaysia particularly, the trends of climate patterns, especially rainfall and temperature have shown extreme changes, which causes floods and heat waves. The extreme climate events have caused economic losses and harmful health effects. Thus, there is a crucial need in analyzing and understanding the climate patterns for proper climate action. This study introduces a dynamic fuzzy graph algorithm, to analyze the rainfall and temperature patterns across 14 different states in Malaysia, from 2010 - 2022. The fuzzy graph is a sophisticated mathematical method that could handle complexities and uncertainties arise from the unpredictable nature of climatic events. The data is modeled in the form of dynamic fuzzy graph and further analyzed using the algorithm developed in MATLAB software. As a result, clusters of patterns are observed in the fuzzy graph coordinated plot, which illustrate the severity of the climate and weather changes of the region and states. Kelantan, Pahang and Sabah show high severity of rainfall distributions, meanwhile, Perak, Negeri Sembilan, Kelantan, Kedah and Sarawak are in the high-severity zone for temperature analysis. The results are compared with a statistical method, namely kernel principal component analysis (kPCA) for verification. The dynamic fuzzy graph algorithm offers an alternative for analysis involving complex and large climate datasets. The dynamics and relations of climate patterns across different regions are able to be identified, which is crucial for effective climate actions.
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References
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