With the increasing occurrence frequency of emergency events, emergency management (EM) has been a very important issue in management science. One of the major activities of EM is to evaluate and select the most desirable emergency alternative(s). This paper proposes a new framework combining the analytic network process (ANP) method, the decision-making trial and evaluation laboratory (DEMATEL) technique, and 2-tuple linguistic technique for order preference by similarity to an ideal solution (TL-TOPSIS) method to solve the emergency alternative evaluation and selection problem. This study has been done in three stages. In the first stage, we use DEMATEL technique to obtain the network relation map (NRM) among emergency alternative evaluation criteria or sub-criteria. In the second stage, we use ANP method to calculate the global weight of each sub-criterion based on the NRM among emergency alternative evaluation sub-criteria. In the third stage, the ratings of emergency alternative with respect to each sub-criterion are described by linguistic items, and the TL-TOPSIS method is used to rank the emergency alternative. Finally, a practical example of urban fire emergency alternative selection is given to illustrate the application of the proposed framework.
Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR), used for monitoring crust deformation, are found to be very promising in earthquake prediction subject to stress-forecasting. However, it is recognized that unless we can give reasonable explanations of these curious precursory phenomena that continue to be serendipitously observed from time to time, such high technology of GPS or InSAR is difficult to be efficiently used. Therefore, a proper model revealing the relation between earthquake evolution and stress variation, such as the phenomena of stress buildup, stress shadow and stress transfer (SSS), is crucial to the GPS or InSAR based earthquake prediction. Here we address this question through a numerical approach of earthquake development using an intuitive physical model with a map-like configuration of discontinuous fault system. The simulation provides a physical basis for the principle of stress-forecasting of earthquakes based on SSS and for the application of GPS or InSAR in earthquake prediction. The observed SSS associated phenomena with images of stress distribution during the failure process can be continuously simulated. It is shown that the SSS are better indicators of earthquake precursors than that of seismic foreshocks, suggesting a predictability of earthquakes based on stress-forecasting strategy. 相似文献
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