{"title":"基于Agent的应急响应动态风险建模方法","authors":"Ma Aixia, Zhou Aidi, A. Asgary, Alain Normand","doi":"10.1109/ICESIT53460.2021.9696775","DOIUrl":null,"url":null,"abstract":"In this paper, Agent in emergency response is summarized, the present tools for agent-based modeling (ABM), the advantages of Anylogic for ABM, and its integrating ABM with GIS function are analyzed. Demonstrating an approach of integrating GIS for ABM with a case is mainly focused on. Through the dynamic risk modelling, the population risk is presented.","PeriodicalId":164745,"journal":{"name":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","volume":"251 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Agent Based Modelling Approach for Dynamic Risk Modelling in Emergency Response\",\"authors\":\"Ma Aixia, Zhou Aidi, A. Asgary, Alain Normand\",\"doi\":\"10.1109/ICESIT53460.2021.9696775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, Agent in emergency response is summarized, the present tools for agent-based modeling (ABM), the advantages of Anylogic for ABM, and its integrating ABM with GIS function are analyzed. Demonstrating an approach of integrating GIS for ABM with a case is mainly focused on. Through the dynamic risk modelling, the population risk is presented.\",\"PeriodicalId\":164745,\"journal\":{\"name\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"volume\":\"251 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICESIT53460.2021.9696775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICESIT53460.2021.9696775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Agent Based Modelling Approach for Dynamic Risk Modelling in Emergency Response
In this paper, Agent in emergency response is summarized, the present tools for agent-based modeling (ABM), the advantages of Anylogic for ABM, and its integrating ABM with GIS function are analyzed. Demonstrating an approach of integrating GIS for ABM with a case is mainly focused on. Through the dynamic risk modelling, the population risk is presented.
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