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: | , , |
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| Format: | Article |
| Published: |
Scientific.Net
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/79965/ https://www.scientific.net/AMM.892.143 |
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| Summary: | 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. |
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