Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/2403
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dc.contributor.authorDrias, Y.-
dc.contributor.authorDrias, H.-
dc.date.accessioned2024-11-05T19:50:45Z-
dc.date.available2024-11-05T19:50:45Z-
dc.date.issued2024-
dc.identifier.isbn9783031671944-
dc.identifier.issn2367-3370-
dc.identifier.urihttps://doi.org/10.1007/978-3-031-67195-1_47-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/2403-
dc.description.abstractIn recent times, our planet has experienced numerous natural disasters across all continents. The damage caused by these disasters has been so extensive that Emergency Medical Services (EMS) proved incapable of handling the situation. In this article, we present a novel approach for urgent disaster transport with the aim of minimizing loss of life. In this context, we are investigating the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN) to cluster the large geographic zone affected by the 2023 earthquake in Türkiye. The clustering is done based on hospitals’ capacity on one hand and damages on the other hand. The ambulance dispatching task is then tackled using a new fuzzy version of Elephant Herding Optimization called FEHO. This approach addresses the challenge of dispatching ambulances to cover emergency locations effectively and optimally in the clustered regions. Experiments conducted on real data demonstrate the effectiveness of our approach in managing emergency transportation and highlight its potential to minimize the number of casualties. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.en_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Networks and Systems -- International Conference on Intelligent and Fuzzy Systems, INFUS 2024 -- 16 July 2024 through 18 July 2024 -- Canakkale -- 318029en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAmbulance dispatchingen_US
dc.subjectDbscanen_US
dc.subjectEmergency transportationen_US
dc.subjectFuzzy elephant herding optimizationen_US
dc.titleFuzzy Elephant Herding Optimization and Dbscan for Emergency Transportation: a Case Study for the 2023 Türkiye Earthquakeen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1007/978-3-031-67195-1_47-
dc.identifier.scopus2-s2.0-85207010616en_US
dc.authorscopusid56440023300-
dc.authorscopusid11538926200-
dc.description.PublishedMonthAğustosen_US
dc.identifier.scopusqualityQ4-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.endpage410en_US
dc.identifier.startpage403en_US
dc.identifier.volume1089 LNNSen_US
dc.department“MEF University”en_US
dc.institutionauthor,,,-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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