دورية أكاديمية
Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events
| العنوان: | Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events |
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| المؤلفون: | Sara Saravi, Roy Kalawsky, Demetrios Joannou, Monica Rivas Casado, Guangtao Fu, Fanlin Meng |
| المصدر: | Water, Vol 11, Iss 5, p 973 (2019) |
| بيانات النشر: | MDPI AG, 2019. |
| سنة النشر: | 2019 |
| المجموعة: | LCC:Hydraulic engineering LCC:Water supply for domestic and industrial purposes |
| مصطلحات موضوعية: | Artificial Intelligence, machine learning, flood, preparedness, resilience, flood resilience, Hydraulic engineering, TC1-978, Water supply for domestic and industrial purposes, TD201-500 |
| الوصف: | The main focus of this paper is the novel use of Artificial Intelligence (AI) in natural disaster, more specifically flooding, to improve flood resilience and preparedness. Different types of flood have varying consequences and are followed by a specific pattern. For example, a flash flood can be a result of snow or ice melt and can occur in specific geographic places and certain season. The motivation behind this research has been raised from the Building Resilience into Risk Management (BRIM) project, looking at resilience in water systems. This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. In this paper, various ML models have been developed and evaluated for classifying floods, i.e., flash flood, lakeshore flood, etc. using current information i.e., weather forecast in different locations. The analytical results show that the Random Forest technique provides the highest accuracy of classification, followed by J48 decision tree and Lazy methods. The classification results can lead to better decision-making on what measures can be taken for prevention and preparedness and thus improve flood resilience. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2073-4441 |
| Relation: | https://www.mdpi.com/2073-4441/11/5/973; https://doaj.org/toc/2073-4441 |
| DOI: | 10.3390/w11050973 |
| URL الوصول: | https://doaj.org/article/ec2042bf83bf460aa52f87e62fff578a |
| رقم الأكسشن: | edsdoj.2042bf83bf460aa52f87e62fff578a |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20734441 |
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| DOI: | 10.3390/w11050973 |