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Fuzzy AHP in a knowledge-based framework for early flood warning

Knowledge is essential for early flood warning as it can save life and property. This paper presents a novel knowledge-based framework based on rainfall, river water level, sediment, cloud distance and cloud strength that contributes to flood in Malaysia as the criteria in the AHP for Multiple Crite...

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Main Authors: Mohd Aris, Teh Noranis, Zolkepli, Maslina, Che Pa, Noraini
Format: Article
Published: Scientific.Net 2019
Online Access:http://psasir.upm.edu.my/id/eprint/79965/
https://www.scientific.net/AMM.892.143
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spelling my.upm.eprints.799652023-04-13T03:40:35Z http://psasir.upm.edu.my/id/eprint/79965/ Fuzzy AHP in a knowledge-based framework for early flood warning Mohd Aris, Teh Noranis Zolkepli, Maslina Che Pa, Noraini Knowledge is essential for early flood warning as it can save life and property. This paper presents a novel knowledge-based framework based on rainfall, river water level, sediment, cloud distance and cloud strength that contributes to flood in Malaysia as the criteria in the AHP for Multiple Criteria Decision Analysis (MCDM). AHP caters complex decisions during flood events in uncertainty condition and provides fast decision making. The proposed framework is applied to the Bernam River Basin dataset located in Selangor, Malaysia. The framework is expected to produce early flood warning to the public. Scientific.Net 2019 Article PeerReviewed Mohd Aris, Teh Noranis and Zolkepli, Maslina and Che Pa, Noraini (2019) Fuzzy AHP in a knowledge-based framework for early flood warning. Applied Mechanics and Materials, 892. pp. 143-149. ISSN 1660-9336; ESSN: 1662-7482 https://www.scientific.net/AMM.892.143 10.4028/www.scientific.net/AMM.892.143
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Knowledge is essential for early flood warning as it can save life and property. This paper presents a novel knowledge-based framework based on rainfall, river water level, sediment, cloud distance and cloud strength that contributes to flood in Malaysia as the criteria in the AHP for Multiple Criteria Decision Analysis (MCDM). AHP caters complex decisions during flood events in uncertainty condition and provides fast decision making. The proposed framework is applied to the Bernam River Basin dataset located in Selangor, Malaysia. The framework is expected to produce early flood warning to the public.
format Article
author Mohd Aris, Teh Noranis
Zolkepli, Maslina
Che Pa, Noraini
spellingShingle Mohd Aris, Teh Noranis
Zolkepli, Maslina
Che Pa, Noraini
Fuzzy AHP in a knowledge-based framework for early flood warning
author_facet Mohd Aris, Teh Noranis
Zolkepli, Maslina
Che Pa, Noraini
author_sort Mohd Aris, Teh Noranis
title Fuzzy AHP in a knowledge-based framework for early flood warning
title_short Fuzzy AHP in a knowledge-based framework for early flood warning
title_full Fuzzy AHP in a knowledge-based framework for early flood warning
title_fullStr Fuzzy AHP in a knowledge-based framework for early flood warning
title_full_unstemmed Fuzzy AHP in a knowledge-based framework for early flood warning
title_sort fuzzy ahp in a knowledge-based framework for early flood warning
publisher Scientific.Net
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/79965/
https://www.scientific.net/AMM.892.143
_version_ 1763298014861983744
score 13.188404

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