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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Shu-Ming Ma,Shu-Shen Zhang,Yu Chen,Guo-Bao Song,Peng Gao.Evaluating Emergency Response Capacity of Chemical Industrial Park Using an Hybrid Fuzzy AHP Method[J].Journal of Harbin Institute Of Technology(New Series),2014,(2):50-56.DOI:10.11916/j.issn.1005-9113.2014.02.008.
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Evaluating Emergency Response Capacity of Chemical Industrial Park Using an Hybrid Fuzzy AHP Method
Author NameAffiliation
Shu-Ming Ma Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian 116024, China 
Shu-Shen Zhang Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian 116024, China 
Yu Chen Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian 116024, China 
Guo-Bao Song Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian 116024, China 
Peng Gao Center for Post-doctoral Studies of Civil Engineering, Harbin Institute of Technology, Harbin 150001, China 
Abstract:
This paper presents an expert-based fuzzy analytic hierarchy process (AHP) model for evaluating emergency response capacity of Chemical Industrial Park (ERCCIP) by jointly using an improved fuzzy preference programming (FPP) and 2-tuple fuzzy linguistic approach. An evaluation index system for ERCCIP is proposed. The weight of sub-criteria and criteria of the evaluation index system for ERCCIP are determined using the improved FPP. And the ratings of sub-criteria are assessed in linguistic values according to the experts’ subjective opinions. Finally, the aggregated ratings of criteria and the overall ERCCIP are calculated.
Key words:  chemical industrial park, emergency response capacity, fuzzy preference programming, 2-tuple linguistic representation model, Fuzzy AHP
DOI:10.11916/j.issn.1005-9113.2014.02.008
Clc Number:X937
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