Change vulnerability forecasting using deep learning algorithm for Southeast Asia

Amelia Ritahani, Ismail and Nur ‘Atikah, Mohd Ali and Junaida, Sulaiman (2018) Change vulnerability forecasting using deep learning algorithm for Southeast Asia. Knowledge Engineering and Data Science (KEDS), 1 (2). pp. 74-78. ISSN 2597-4602 (Print); 2597-4637 (Online). (Published)

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Climate change is expected to change people’s livelihood in significant ways. Several vulnerability factors and readiness factors used for measuring the prediction index of that particular country on how vulnerable of a country towards global change. Primary data was collected from University of Notre Dame Global Adaptation Index (ND-GAIN). The data has been trained for the forecasting purpose with support from the validated statistical analysis. The summary of the predicted index is visualized using machine learning tools. The results developed the correlation between vulnerability and readiness factors and shows the stability of the country towards climate change. The framework is applied to synthesize findings from Prediction index studies in South East Asia in dealing with vulnerability to climate change.

Item Type: Article
Uncontrolled Keywords: Deep learning; Forecasting; Climate change
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 10 Oct 2018 06:27
Last Modified: 10 Oct 2018 06:27
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