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Decision Support System for Flood Disaster Mitigation

Nuka Dumle Nwiabu, Gift Oyekuodi Aselemi in Information Sciences

International Journal of Applied Information Systems
Year of Publication: 2019
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Nuka Dumle Nwiabu, Gift Oyekuodi Aselemi
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  1. Nuka Dumle Nwiabu and Gift Oyekuodi Aselemi. Decision Support System for Flood Disaster Mitigation. International Journal of Applied Information Systems 12(21):5-13, June 2019. URL, DOI BibTeX

    	author = "Nuka Dumle Nwiabu and Gift Oyekuodi Aselemi",
    	title = "Decision Support System for Flood Disaster Mitigation",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "June, 2019",
    	volume = 12,
    	number = 21,
    	month = "June",
    	year = 2019,
    	issn = "2249-0868",
    	pages = "5-13",
    	url = "",
    	doi = "10.5120/ijais2019451803",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


The catastrophic effects of past flooding such as the 2012 flood that occurred in Nigeria have underlined the importance of making timely mitigation decisions in advance of a catastrophic Events. Decision Support System (DSS) help users settle on compelling decisions in flood disaster mitigation and prevention. Decision Support Systems are computer based systems that are aimed at assisting decision-makers in making productive, agile, innovative and reputable decisions. The work presents a decision support system using Fuzzy logic, the wind speed and temperature data were obtained from Nigerian Meteorological Agency (NIMET) and Climate_Data are classified into very low, low, normal, high, very high, and extremely high to denote the amount of rainfall. The input data were used in DSS model to test the system in order to evaluate the amount rainfall so that predictions can be made. The results were promising indicating the amount of rainfall that can cause severe flooding.


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Decision Support System; Flood Mitigation; Disaster Management; Fuzzy logic