基于案例的应急管理推理系统:近期发展综述

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2021-07-12 DOI:10.1080/0952813X.2021.1952654

Walid Bannour, A. Maalel, H. Ghézala

{"title":"基于案例的应急管理推理系统:近期发展综述","authors":"Walid Bannour, A. Maalel, H. Ghézala","doi":"10.1080/0952813X.2021.1952654","DOIUrl":null,"url":null,"abstract":"ABSTRACT With the frequent occurrence of natural and man-made disasters, emergency management has become an active research field aiming at saving lives and reducing environmental and economic losses. Due to the complexity of crisis situations, emergency managers need to be assisted in making critical and effective decisions. Case-based reasoning (CBR) methodology has been widely adopted to support emergency decision makers in their tasks. This paper presents a comprehensive literature review of recent emergency management CBR systems reported in peer-reviewed journals and ICCBR conference proceedings between 2000 and 2020. Recent development trends of emergency management CBR systems are identified in terms of their purposes, application contexts and techniques used for their development. Finally, opportunities to improve emergency management CBR systems are outlined.","PeriodicalId":15677,"journal":{"name":"Journal of Experimental & Theoretical Artificial Intelligence","volume":"23 1","pages":"35 - 58"},"PeriodicalIF":1.7000,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Emergency Management Case-Based Reasoning Systems: A Survey of Recent Developments\",\"authors\":\"Walid Bannour, A. Maalel, H. Ghézala\",\"doi\":\"10.1080/0952813X.2021.1952654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT With the frequent occurrence of natural and man-made disasters, emergency management has become an active research field aiming at saving lives and reducing environmental and economic losses. Due to the complexity of crisis situations, emergency managers need to be assisted in making critical and effective decisions. Case-based reasoning (CBR) methodology has been widely adopted to support emergency decision makers in their tasks. This paper presents a comprehensive literature review of recent emergency management CBR systems reported in peer-reviewed journals and ICCBR conference proceedings between 2000 and 2020. Recent development trends of emergency management CBR systems are identified in terms of their purposes, application contexts and techniques used for their development. Finally, opportunities to improve emergency management CBR systems are outlined.\",\"PeriodicalId\":15677,\"journal\":{\"name\":\"Journal of Experimental & Theoretical Artificial Intelligence\",\"volume\":\"23 1\",\"pages\":\"35 - 58\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2021-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Experimental & Theoretical Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/0952813X.2021.1952654\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental & Theoretical Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/0952813X.2021.1952654","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}

引用次数: 2

摘要

随着自然灾害和人为灾害的频繁发生，以挽救生命、减少环境和经济损失为目标的应急管理已成为一个活跃的研究领域。由于危机局势的复杂性，需要协助应急管理人员作出关键和有效的决定。基于案例的推理(CBR)方法已被广泛采用，以支持应急决策者的任务。本文对2000年至2020年间同行评议期刊和ICCBR会议论文集中报道的近期应急管理CBR系统进行了全面的文献综述。从应急管理CBR系统的目的、应用环境和开发技术等方面确定了应急管理CBR系统的最新发展趋势。最后，概述了改进应急管理CBR系统的机会。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Emergency Management Case-Based Reasoning Systems: A Survey of Recent Developments

ABSTRACT With the frequent occurrence of natural and man-made disasters, emergency management has become an active research field aiming at saving lives and reducing environmental and economic losses. Due to the complexity of crisis situations, emergency managers need to be assisted in making critical and effective decisions. Case-based reasoning (CBR) methodology has been widely adopted to support emergency decision makers in their tasks. This paper presents a comprehensive literature review of recent emergency management CBR systems reported in peer-reviewed journals and ICCBR conference proceedings between 2000 and 2020. Recent development trends of emergency management CBR systems are identified in terms of their purposes, application contexts and techniques used for their development. Finally, opportunities to improve emergency management CBR systems are outlined.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving