Survey of computational intelligence as basis to big flood management: challenges, research directions and future work
| Autor: | Sina Ardabili, Farnaz Fotovatikhah, Manuel Herrera, Shahaboddin Shamshirband, Md. Jalil Piran, Kwok Wing Chau |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
flood management system
Engineering General Computer Science Flood myth business.industry fungi 0208 environmental biotechnology Flooding (psychology) Big data food and beverages Computational intelligence 02 engineering and technology natural hazard Debris 020801 environmental engineering Work (electrical) Hazardous waste lcsh:TA1-2040 Modeling and Simulation Natural hazard computational intelligence business lcsh:Engineering (General). Civil engineering (General) Environmental planning |
| Zdroj: | Engineering Applications of Computational Fluid Mechanics, Vol 12, Iss 1, Pp 411-437 (2018) Fotovatikhah, F, Herrera, M, Shamshirband, S, Chau, K, Ardabili, S F & Piran, M J 2018, ' Survey of computational intelligence as basis to big flood management: challenges, research directions and future work ', Engineering Applications of Computational Fluid Mechanics, vol. 12, no. 1, pp. 411-437 . https://doi.org/10.1080/19942060.2018.1448896 |
| ISSN: | 1994-2060 |
| DOI: | 10.1080/19942060.2018.1448896 |
| Popis: | Flooding produces debris and waste including liquids, dead animal bodies and hazardous materials such as hospital waste. Debris causes serious threats to people’s health and can even block the roads used to give emergency aid, worsening the situation. To cope with these issues, flood management systems (FMSs) are adopted for the decision-making process of critical situations. Nowadays, conventional artificial intelligence and computational intelligence (CI) methods are applied to early flood event detection, having a low false alarm rate. City authorities can then provide quick and efficient response in post-disaster scenarios. This paper aims to present a comprehensive survey about the application of CI-based methods in FMSs. CI approaches are categorized as single and hybrid methods. The paper also identifies and introduces the most promising approaches nowadays with respect to the accuracy and error rate for flood debris forecasting and management. Ensemble CI approaches are shown to be highly efficient for flood prediction. |
| Databáze: | OpenAIRE |
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