Risk Early-Warning Method for Natural Disasters Based on Integration of Entropy and DEA Model

Fengshan Wang, Yan Cao, Meng Liu

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DOI: 10.4236/am.2011.21003                

Abstract

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and DEA model, whose steps were put forward. On the basis of standard risk early-warning DEA model of natural disasters, weight coefficient of risk early-warning factors was determined with Information Entropy method, which improved standard risk early-warning DEA model with non-Archimedean infinitesimal, and established risk early-warning preference DEA model based on integrated entropy weight and DEA Model. Finally, model was applied into landslide risk early-warning case in earthquake-damaged emergency process on slope engineering, which exemplified the outcome could reflect more risk information than the method of standard DEA model, and reflected the rationality, feasibility, and impersonality, revealing its better ability on comprehensive safety and structure risk.

Keywords

Entropy, Data Envelopment Analysis, Comprehensive Integration, Essential Attribute, Risk Early-Warning, Natural Disaster

Conflicts of Interest

The authors declare no conflicts of interest.

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