A Rapid Data Processing and Assessing Model for “Scenario-Response” Types Natural Disaster Emergency Alternatives

Daji Ergu (), Gang Kou () and Yong Zhang ()
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Daji Ergu: University of Electronic Science and Technology of China
Gang Kou: University of Electronic Science and Technology of China
Yong Zhang: University of Electronic Science and Technology of China

Chapter Chapter 7 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 61-69 from Springer

Abstract: Abstract In the processes of assessing the emergency alternatives of “scenario-response” types natural disaster by Analytic Hierarchy (Network) Process (AHP/ANP), the elements or data of the scenario itself, the real-time data and the trend factors of the evolution of “scenario-response” types natural disaster emergencies etc. are usually inconsistent and intangible, which increase the difficulty of emergency alternatives assessment and delay the speed of emergency response. Therefore, in this paper, a logarithm mean induced bias matrix (LMIBM) model is proposed to quickly process the inconsistent data of “scenario-response” type’s natural disaster when AHP/ANP is used to assess the natural disaster emergency alternatives and evolution trend factors of natural disaster emergency accidents. Two numerical examples are used to illustrate the proposed model, and the results show that LMIBM can quickly identify the inconsistent natural disaster data and improve the speed of emergency alternatives assessment and natural disaster response by AHP/ANP.

Keywords: AHP/ANP; Data processing; Emergency alternatives assessment; Logarithm mean induced bias matrix; Natural disaster (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38391-5_7

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DOI: 10.1007/978-3-642-38391-5_7

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