Survey of computational intelligence as basis to big flood management: challenges, research directions and future work

Engineering Applications of Computational Fluid Mechanics

Kwok-wing Chau¹  Farnaz Fotovatikhah²  Md. Jalil Piran³  Shahaboddin Shamshirband⁴  Manuel Herrera⁵  Sina Faizollahzadeh Ardabili⁶ 

[1] Hong Kong Polytechnic University;SPM Lab;Sejong University;Ton Duc Thang University;University of Bath;University of Mohaghegh Ardabili;

关键词: Big data;    flood management system;    computational intelligence;    natural hazard;   

DOI  :  10.1080/19942060.2018.1448896

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown