A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules
Over the last decade, flooding has been one of catastrophic disaster which causes economic damage, lost life and environmental deprivations. The need for flood prediction is rising since the decision maker lacks intelligent tools to predict flood areas. The data mining and geospatial visualization w...
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Asian Research Publishing Network
2016
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my-unisza-ir.74052022-09-13T05:47:11Z http://eprints.unisza.edu.my/7405/ A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules Azwa, Abdul Aziz Engku Fadzli Hasan, Syed Abdullah Julaily Aida, Jusoh GE Environmental Sciences Over the last decade, flooding has been one of catastrophic disaster which causes economic damage, lost life and environmental deprivations. The need for flood prediction is rising since the decision maker lacks intelligent tools to predict flood areas. The data mining and geospatial visualization will test the temporal data which include river flow and rainfall data to find patterns and new information which then will use to predict areas that expose to flood. Since Terengganu situated at east peninsular, every year in October to March will be having heavy rainfall and increasing of sea levels. To this extent, we propose a framework to support flood prediction which the outcome will intention to better manage floods through prevention, protection and emergency response. Asian Research Publishing Network 2016 Article PeerReviewed image en http://eprints.unisza.edu.my/7405/1/FH02-FIK-16-06057.jpg Azwa, Abdul Aziz and Engku Fadzli Hasan, Syed Abdullah and Julaily Aida, Jusoh (2016) A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules. Journal of Theoretical and Applied Information Technology, 87 (3). pp. 512-519. ISSN 19928645 [P] |
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GE Environmental Sciences Azwa, Abdul Aziz Engku Fadzli Hasan, Syed Abdullah Julaily Aida, Jusoh A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
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Over the last decade, flooding has been one of catastrophic disaster which causes economic damage, lost life and environmental deprivations. The need for flood prediction is rising since the decision maker lacks intelligent tools to predict flood areas. The data mining and geospatial visualization will test the temporal data which include river flow and rainfall data to find patterns and new information which then will use to predict areas that expose to flood. Since Terengganu situated at east peninsular, every year in October to March will be having heavy rainfall and increasing of sea levels. To this extent, we propose a framework to support flood prediction which the outcome will intention to better manage floods through prevention, protection and emergency response. |
format |
Article |
author |
Azwa, Abdul Aziz Engku Fadzli Hasan, Syed Abdullah Julaily Aida, Jusoh |
author_facet |
Azwa, Abdul Aziz Engku Fadzli Hasan, Syed Abdullah Julaily Aida, Jusoh |
author_sort |
Azwa, Abdul Aziz |
title |
A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
title_short |
A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
title_full |
A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
title_fullStr |
A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
title_full_unstemmed |
A conceptual framework for predicting flood area in Terengganu during monsoon season using association rules |
title_sort |
conceptual framework for predicting flood area in terengganu during monsoon season using association rules |
publisher |
Asian Research Publishing Network |
publishDate |
2016 |
url |
http://eprints.unisza.edu.my/7405/1/FH02-FIK-16-06057.jpg http://eprints.unisza.edu.my/7405/ |
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1744358600563752960 |
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13.209306 |