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A novel case adaptation method based on differential evolution algorithm for disaster emergency
When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptati...
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Published in: | Applied soft computing 2020-07, Vol.92, p.106306, Article 106306 |
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container_title | Applied soft computing |
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creator | Yu, Xiaobing Li, Chenliang Zhao, Wen-Xuan Chen, Hong |
description | When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptation is the core. To improve the adaptation, a hybrid mutation operator is implemented, and a new differential evolution (DE) algorithm is developed. An adaptation method based on the proposed algorithm is put forward to achieve case adaptation in the CBR system. The comparison results have shown that the proposed algorithm is superior compared with the state-of-art algorithms. Then, experiments of CBR have revealed that the adaptation method can effectively generate appropriate solutions with the help of the proposed algorithm. |
doi_str_mv | 10.1016/j.asoc.2020.106306 |
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Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptation is the core. To improve the adaptation, a hybrid mutation operator is implemented, and a new differential evolution (DE) algorithm is developed. An adaptation method based on the proposed algorithm is put forward to achieve case adaptation in the CBR system. The comparison results have shown that the proposed algorithm is superior compared with the state-of-art algorithms. Then, experiments of CBR have revealed that the adaptation method can effectively generate appropriate solutions with the help of the proposed algorithm.</description><identifier>ISSN: 1568-4946</identifier><identifier>EISSN: 1872-9681</identifier><identifier>DOI: 10.1016/j.asoc.2020.106306</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Adaptation ; Case-based reasoning ; Differential evolution algorithm ; Disaster emergency</subject><ispartof>Applied soft computing, 2020-07, Vol.92, p.106306, Article 106306</ispartof><rights>2020 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c300t-138f50661d0750dc602d227c408fa8ce9b618f291253189024b9bbef06798e3d3</citedby><cites>FETCH-LOGICAL-c300t-138f50661d0750dc602d227c408fa8ce9b618f291253189024b9bbef06798e3d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Yu, Xiaobing</creatorcontrib><creatorcontrib>Li, Chenliang</creatorcontrib><creatorcontrib>Zhao, Wen-Xuan</creatorcontrib><creatorcontrib>Chen, Hong</creatorcontrib><title>A novel case adaptation method based on differential evolution algorithm for disaster emergency</title><title>Applied soft computing</title><description>When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptation is the core. To improve the adaptation, a hybrid mutation operator is implemented, and a new differential evolution (DE) algorithm is developed. An adaptation method based on the proposed algorithm is put forward to achieve case adaptation in the CBR system. The comparison results have shown that the proposed algorithm is superior compared with the state-of-art algorithms. Then, experiments of CBR have revealed that the adaptation method can effectively generate appropriate solutions with the help of the proposed algorithm.</description><subject>Adaptation</subject><subject>Case-based reasoning</subject><subject>Differential evolution algorithm</subject><subject>Disaster emergency</subject><issn>1568-4946</issn><issn>1872-9681</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kM1KAzEUhYMoWKsv4CovMDXJzGQScFOKf1Bwo-uQSW7alJlJSWLBtzdjXbu69x7OuRw-hO4pWVFC-cNhpVMwK0bYLPCa8Au0oKJjleSCXpa95aJqZMOv0U1KB1JCkokFUms8hRMM2OgEWFt9zDr7MOER8j5Y3BfZ4nJb7xxEmLLXA4ZTGL5-bXrYhejzfsQuxGJKOmWIGEaIO5jM9y26cnpIcPc3l-jz-elj81pt31_eNuttZWpCckVr4VrCObWka4k1nDDLWGcaIpwWBmTPqXBMUtbWVEjCml72PTjCOymgtvUSsfNfE0NKEZw6Rj_q-K0oUTMidVAzIjUjUmdEJfR4DkFpdvIQVTK-tAbrI5isbPD_xX8AdfNwRQ</recordid><startdate>202007</startdate><enddate>202007</enddate><creator>Yu, Xiaobing</creator><creator>Li, Chenliang</creator><creator>Zhao, Wen-Xuan</creator><creator>Chen, Hong</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>202007</creationdate><title>A novel case adaptation method based on differential evolution algorithm for disaster emergency</title><author>Yu, Xiaobing ; Li, Chenliang ; Zhao, Wen-Xuan ; Chen, Hong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c300t-138f50661d0750dc602d227c408fa8ce9b618f291253189024b9bbef06798e3d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adaptation</topic><topic>Case-based reasoning</topic><topic>Differential evolution algorithm</topic><topic>Disaster emergency</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Xiaobing</creatorcontrib><creatorcontrib>Li, Chenliang</creatorcontrib><creatorcontrib>Zhao, Wen-Xuan</creatorcontrib><creatorcontrib>Chen, Hong</creatorcontrib><collection>CrossRef</collection><jtitle>Applied soft computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Xiaobing</au><au>Li, Chenliang</au><au>Zhao, Wen-Xuan</au><au>Chen, Hong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel case adaptation method based on differential evolution algorithm for disaster emergency</atitle><jtitle>Applied soft computing</jtitle><date>2020-07</date><risdate>2020</risdate><volume>92</volume><spage>106306</spage><pages>106306-</pages><artnum>106306</artnum><issn>1568-4946</issn><eissn>1872-9681</eissn><abstract>When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of the most effective approaches to support disaster emergency management. CBR takes good use of historical case data, which is one of the typical data-driven decision-making methods. Among the steps of CBR, adaptation is the core. To improve the adaptation, a hybrid mutation operator is implemented, and a new differential evolution (DE) algorithm is developed. An adaptation method based on the proposed algorithm is put forward to achieve case adaptation in the CBR system. The comparison results have shown that the proposed algorithm is superior compared with the state-of-art algorithms. Then, experiments of CBR have revealed that the adaptation method can effectively generate appropriate solutions with the help of the proposed algorithm.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.asoc.2020.106306</doi></addata></record> |
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subjects | Adaptation Case-based reasoning Differential evolution algorithm Disaster emergency |
title | A novel case adaptation method based on differential evolution algorithm for disaster emergency |
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