This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation. 相似文献
Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Na?ve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Na?ve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%). 相似文献
Acta Geotechnica - Helical anchors are bearing elements that can resist uplift loads by a combination of shaft and helical plate bearing. The application of helical piles as offshore wind turbine... 相似文献
Natural Hazards - Spatial information on flood risk and flood-related crop losses is important in flood mitigation and risk management in agricultural watersheds. In this study, loss of water bound... 相似文献
Natural Hazards - Spatial–temporal changes of land surface parameters (land cover change, net primary production, and vegetation phenology) affect the characteristics of atmospheric dust.... 相似文献
Natural Hazards - Rapid urbanization has become and will continue to be an inevitable and inescapable phenomenon in the developing world. Unplanned expansion of cities and the impacts of climate... 相似文献
Natural Hazards - Due to the need to reduce the flooding disaster, river streamflow prediction is required to be enhanced by the aid of deep learning algorithms. To achieve accurate model of... 相似文献
Natural Hazards - Climate change is likely to increase the risk of drought which impacts on health are not quite known well due to its creeping nature. This study maps the publications on the... 相似文献
Bulletin of Earthquake Engineering - A structure may be subject to several aftershocks after a mainshock. In many seismic design provisions, the effect of the seismic sequences is either not... 相似文献
In nonlinear dynamic structural analysis, a suite of pulse-like ground motions is required for the performance-based design of structures near active faults. The dissimilarity in the amplitude and frequency content of the earthquake time series referred to nonstationary properties in temporal and spectral, respectively. An approach is proposed based on the nonstationary properties of the far-field records and the seismological information in an event for simulating pulse-like records. The pulse-like earthquake time history is estimated via the superposition of the residual part of the earthquake with the estimated pulse. The wavelet-based Hilbert transform is utilized to characterize the nonstationary properties, the instantaneous amplitude, and frequencies of far-field records to model residual part. The effects of near-fault and pulse are estimated based on the seismological properties of the region. The validation of the procedure is indicated by comparing simulated time-series, response spectra, and Arias intensity with recorded pulse-like records in two different earthquakes in California; the Mw 6.7 1994 Northridge and the Mw 6.5 1979 Imperial valley.