Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan
Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and...
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Veröffentlicht in: | Journal of intelligent & fuzzy systems 2021-01, Vol.40 (6), p.11007-11022 |
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container_title | Journal of intelligent & fuzzy systems |
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creator | Yu, Xiaobing Yu, Xianrui Zhang, Xueying |
description | Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications. |
doi_str_mv | 10.3233/JIFS-202132 |
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Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-202132</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Adaptation ; Algorithms ; Disaster management ; Disasters ; Emergency management ; Emergency plans ; Emergency preparedness ; Emergency response ; Fuzzy logic ; Reasoning ; Search algorithms</subject><ispartof>Journal of intelligent & fuzzy systems, 2021-01, Vol.40 (6), p.11007-11022</ispartof><rights>Copyright IOS Press BV 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c261t-1a5c0904c30d21c6bc28bf81e78f1486e689e61b2f1c8a61c146fa4387250a533</citedby><cites>FETCH-LOGICAL-c261t-1a5c0904c30d21c6bc28bf81e78f1486e689e61b2f1c8a61c146fa4387250a533</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids></links><search><creatorcontrib>Yu, Xiaobing</creatorcontrib><creatorcontrib>Yu, Xianrui</creatorcontrib><creatorcontrib>Zhang, Xueying</creatorcontrib><title>Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan</title><title>Journal of intelligent & fuzzy systems</title><description>Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications.</description><subject>Adaptation</subject><subject>Algorithms</subject><subject>Disaster management</subject><subject>Disasters</subject><subject>Emergency management</subject><subject>Emergency plans</subject><subject>Emergency preparedness</subject><subject>Emergency response</subject><subject>Fuzzy logic</subject><subject>Reasoning</subject><subject>Search algorithms</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNotkNFKwzAUhoMoOKdXvkDAS6nmJGmaXcpwOhl4oV6X0zTpMrqmJp2wPb2VenPOD__H4fARcgvsQXAhHt_Wq4-MMw6Cn5EZ6CLP9EIV52NmSmbApbokVyntGIMi52xG_BKTzapx1DRaTKHzXUOxxn7AwYeOTtUY3OF0OtIm4o-fKmxpshjNlmLbhOiH7Z66EGntE6bBRmr3Nja2M0fat9hdkwuHbbI3_3tOvlbPn8vXbPP-sl4-bTLDFQwZYG7YgkkjWM3BqMpwXTkNttAOpFZW6YVVUHEHRqMCA1I5lEIXPGeYCzEnd9PdPobvg01DuQuHOH6bSp6PHNOay5G6nygTQ0rRurKPfo_xWAIr_1yWfy7LyaX4BURfZ5c</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Yu, Xiaobing</creator><creator>Yu, Xianrui</creator><creator>Zhang, Xueying</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210101</creationdate><title>Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan</title><author>Yu, Xiaobing ; Yu, Xianrui ; Zhang, Xueying</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-1a5c0904c30d21c6bc28bf81e78f1486e689e61b2f1c8a61c146fa4387250a533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptation</topic><topic>Algorithms</topic><topic>Disaster management</topic><topic>Disasters</topic><topic>Emergency management</topic><topic>Emergency plans</topic><topic>Emergency preparedness</topic><topic>Emergency response</topic><topic>Fuzzy logic</topic><topic>Reasoning</topic><topic>Search algorithms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Xiaobing</creatorcontrib><creatorcontrib>Yu, Xianrui</creatorcontrib><creatorcontrib>Zhang, Xueying</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent & fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Xiaobing</au><au>Yu, Xianrui</au><au>Zhang, Xueying</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan</atitle><jtitle>Journal of intelligent & fuzzy systems</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>40</volume><issue>6</issue><spage>11007</spage><epage>11022</epage><pages>11007-11022</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. 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subjects | Adaptation Algorithms Disaster management Disasters Emergency management Emergency plans Emergency preparedness Emergency response Fuzzy logic Reasoning Search algorithms |
title | Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan |
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