Forecasting Demand for Emergency Material Classification Based on Casualty Population
Accurately forecasting emergency material demand during the initial stages of disaster response is challenging due to communication disruptions and data scarcity. This study proposes a hybrid model integrating regression analysis and intelligent analysis to estimate casualties and predict emergency...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/13/6/478 |
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| _version_ | 1849425614364213248 |
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| author | Jianliang Yang Kun Zhang Hanping Hou Na Li |
| author_facet | Jianliang Yang Kun Zhang Hanping Hou Na Li |
| author_sort | Jianliang Yang |
| collection | DOAJ |
| description | Accurately forecasting emergency material demand during the initial stages of disaster response is challenging due to communication disruptions and data scarcity. This study proposes a hybrid model integrating regression analysis and intelligent analysis to estimate casualties and predict emergency supply needs indirectly. A case study of five earthquake-affected villages validates the model, using building collapse rates and population data to calculate casualties and determine the demand for essential supplies, including food, water, medicine, and tents. The findings demonstrate that the proposed approach effectively addresses the “black box” condition by utilizing correction factors for population density, disaster preparedness, and emergency response capacity, providing a structured framework for rapid and accurate demand forecasting in disaster scenarios. |
| format | Article |
| id | doaj-art-9639c8fcbe034e6ab7315aca70d557b0 |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-9639c8fcbe034e6ab7315aca70d557b02025-08-20T03:29:43ZengMDPI AGSystems2079-89542025-06-0113647810.3390/systems13060478Forecasting Demand for Emergency Material Classification Based on Casualty PopulationJianliang Yang0Kun Zhang1Hanping Hou2Na Li3School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, ChinaAccurately forecasting emergency material demand during the initial stages of disaster response is challenging due to communication disruptions and data scarcity. This study proposes a hybrid model integrating regression analysis and intelligent analysis to estimate casualties and predict emergency supply needs indirectly. A case study of five earthquake-affected villages validates the model, using building collapse rates and population data to calculate casualties and determine the demand for essential supplies, including food, water, medicine, and tents. The findings demonstrate that the proposed approach effectively addresses the “black box” condition by utilizing correction factors for population density, disaster preparedness, and emergency response capacity, providing a structured framework for rapid and accurate demand forecasting in disaster scenarios.https://www.mdpi.com/2079-8954/13/6/478emergency suppliessurvival rate of casualtiesmaterial classificationdemand forecasting |
| spellingShingle | Jianliang Yang Kun Zhang Hanping Hou Na Li Forecasting Demand for Emergency Material Classification Based on Casualty Population Systems emergency supplies survival rate of casualties material classification demand forecasting |
| title | Forecasting Demand for Emergency Material Classification Based on Casualty Population |
| title_full | Forecasting Demand for Emergency Material Classification Based on Casualty Population |
| title_fullStr | Forecasting Demand for Emergency Material Classification Based on Casualty Population |
| title_full_unstemmed | Forecasting Demand for Emergency Material Classification Based on Casualty Population |
| title_short | Forecasting Demand for Emergency Material Classification Based on Casualty Population |
| title_sort | forecasting demand for emergency material classification based on casualty population |
| topic | emergency supplies survival rate of casualties material classification demand forecasting |
| url | https://www.mdpi.com/2079-8954/13/6/478 |
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