China Safety Science Journal ›› 2019, Vol. 29 ›› Issue (7): 156-163.doi: 10.16265/j.cnki.issn1003-3033.2019.07.025

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Study on double combination evaluation method of urban comprehensive disaster risk

XIA Chenhong1,2, WANG Wei1,2, MA Donghui1,2, SU Jingyu1,2   

  1. 1 College of Architecture and Urban Planning, Beijing University of Technology, Beijing 100124, China;
    2 Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing 100124, China
  • Received:2019-03-18 Revised:2019-05-25 Online:2019-07-28 Published:2020-10-21

Abstract: In order to solve the problem of inconsistency in the evaluation results obtained by different single methods, an evaluation idea based on the combination of sequencing values and evaluation values was proposed. Firstly, seven typical single methods were used to evaluate the comprehensive disaster risks of 31 provinces, autonomous regions and municipalities directly under the central government in China, and the basic evaluation of urban comprehensive disaster risk was carried out based on the evaluation results by each method. Then using KENDALL concordance coefficient, Spearman grade correlation coefficient and comprehensive support coefficient as criteria of consistency test, the close correlation degree between each single evaluation method was calculated. Besides, the double evaluation model was applied to combine the single evaluation results and repeat the tests. Finally, the highly coordinated ranking and evaluation values of comprehensive disaster risk were obtained. The results show that the dual combination evaluation method can effectively reduce the random deviation and systematic error in the evaluation process, and obtain the risk assessment value and ranking value of high convergence and credibility, which provides a new idea for the assessment of urban comprehensive disaster risk.

Key words: comprehensive disaster risk, consistency check, circular correction idea, support degree concept, double combination model

CLC Number: