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Hybrid spatial data mining methods for site selection of emergency response centers

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  • Bo Fan

Abstract

Traditional methods for site selection fail to give reasonable weight to the potential risk grade of different locations. Consequently, site selection does not highlight locations with higher risk grades. Thus, a hybrid analytical method for the site selection of emergency response centers is proposed. First, spatial predicates are incorporated into emergency event analysis. These spatial predicates describe the spatial relationships between emergency locations and surrounding objects. A spatial data association mining method is then developed to identify the correlation rules that contain emergency information and geographical factors. Such rules act as the weight adding mechanism on different urban buildings, such that every spatial object is assigned a risk grade based on these rules. Furthermore, a simulated annealing algorithm is developed by incorporating the weight adding method to locate the optimal sites for emergency centers. A series of experiments is conducted, and the results demonstrate the efficiency of the proposed hybrid method. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Bo Fan, 2014. "Hybrid spatial data mining methods for site selection of emergency response centers," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 643-656, January.
    • Handle: RePEc:spr:nathaz:v:70:y:2014:i:1:p:643-656
    DOI: 10.1007/s11069-013-0833-5
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    References listed on IDEAS

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    Cited by:

    1. Kadir Kaan GÖNCÜ & Onur ÇETIN, 2022. "Evaluation Of Location Selection Criteria For Coordination Management Centers And Logistic Support Units In Disaster Areas With Ahp Method," Prizren Social Science Journal, SHIKS, vol. 6(2), pages 15-23, August.
    2. Ming Zhao & Qiuwen Chen, 2015. "Risk-based optimization of emergency rescue facilities locations for large-scale environmental accidents to improve urban public safety," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 163-189, January.
    3. S. M. Amin Hosseini & Rama Ghalambordezfooly & Albert de la Fuente, 2022. "Sustainability Model to Select Optimal Site Location for Temporary Housing Units: Combining GIS and the MIVES–Knapsack Model," Sustainability, MDPI, vol. 14(8), pages 1-23, April.

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