Evaluation framework for smart disaster response systems in uncertainty environment

被引:49
|
作者
Abdel-Basset, Mohamed [1 ]
Mohamed, Rehab [1 ]
Elhoseny, Mohamed [2 ]
Chang, Victor [3 ]
机构
[1] Zagazig Univ, Fac Comp & Informat, Zagazig 44519, Egypt
[2] Mansoura Univ, Fac Comp & Informat, El Gomhouria St, Dakahlia 35516, Egypt
[3] Teesside Univ, Sch Comp Engn & Digital Technol, Middlesbrough, Cleveland, England
关键词
Smart disaster response systems; Plithogenic; Uncertainty; MCDM; Performance evaluation;
D O I
10.1016/j.ymssp.2020.106941
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
As a major priority to get better resource utilization and to ensure a high quality of life, research on smart disaster response systems (smart DRS) that based on information and communication technology (Icr) has been widespread. It's imperative for smart cities to have smart disaster response systems so they can easily manage natural disasters efficiently such as tsunamis, earthquakes, and hurricanes. Lately, the Internet of Things (loT) provided several solutions to confront the disaster concerns such as early cautions, remote controlling, data analysis and knowledge building. To evaluate the performance of the smart disaster response systems, there are a group of criteria that need to be measured. This study proposed an integrated framework to evaluate the performance of smart disaster response systems under uncertainty. Due to ensure a more accurate evaluation process, the proposed framework is based on plithogenic set theory that handles ambiguity and uncertainty in evaluation by considering the contradiction degree between the evaluation criteria. The problem of performance evaluation of the smart disaster response systems is formulated as a multi-criteria decision-making problem. The proposed framework is constructed using three common MCDM methods which is AHP, TOSIS, and VIKOR. Five smart disaster response systems will be evaluated in order to improve the reliability of the proposed framework. (C) 2020 Elsevier Ltd. All rights reserved.
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页数:18
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