Decision Support System For Malaysia Flood Management: Intelligent Vs Effectiveness

Mohd Ekhwan, Toriman (2014) Decision Support System For Malaysia Flood Management: Intelligent Vs Effectiveness. In: Malaysia Water Resources Management Forum 2014, 09-10 June 2014, Dewan Siantan, Putrajaya.

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Abstract

Flood situation required fast and accurate decision as every decision is very critical to save human lives. Naturally, during this situation humans made decision based on their past experiences by which their nerves and brain system will perceive the situation and mapped with their experiences to produce action. This naturalistic decision making approach has been one of the attention in flood management research. With computer advance, making decision and decision making on flood management become easier. Integrating human knowledge with modeling tools, an intelligent decision support system (DSS) assist decision makers during different phases of flood management. However, the DSS developed always become a debate among the decision makers, modeler, hydrologists, etc. Two questions are mostly discussed- (1) how intelligent and (2) How effective the DSS. In this paper a conceptual model of DSS for flood management is discussed. The intelligent and effectiveness of the DSS will be elaborated in its capability to selecting suitable flood damage reduction options (using an expert system approach); forecasting or nowcasting floods; modeling the operation of flood control structures; and describing the impacts (area flooded and damage) of floods in time and space. Finally, this paper suggests way forwards on the potential of DSS intelligent as an effective tool to simulate human good decision on flood management in Malaysia.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: Faculty of Bio-resources & Food Industry
Depositing User: Muhammad Akmal Azhar
Date Deposited: 21 Oct 2020 03:31
Last Modified: 24 Nov 2020 07:27
URI: http://eprints.unisza.edu.my/id/eprint/314

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