Making Inferences About Settlements from Satellite Images Using Glowworm Swarm Optimization

Basit Öğe Kaydı
dc.authoridElen, Abdullah/0000-0003-1644-0476
dc.authoridKahramanli Ornek, Humar/0000-0003-2336-7924
dc.contributor.authorAvuclu, Emre
dc.contributor.authorElen, Abdullah
dc.contributor.authorOrnek, Humar Kahramanli
dc.date.accessioned2024-09-29T15:54:53Z
dc.date.available2024-09-29T15:54:53Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractOptimization is the process of choosing the best one among existing possibilities under particular circumstances in a problem. There are various algorithms for optimization problems nowadays. Metaheuristic algorithms are the algorithms giving almost optimum solutions at an acceptable duration for the problems of large dimension. Heuristic optimization algorithms with general aim are evaluated in different groups. Swarm intelligence-based optimization algorithms were developed through examining the behaviors and movements of living flocks such as birds, fish, cats, and bees. With these algorithms, some estimating processes are carried out successfully in all areas. In this study a new approach was presented with a novel idea, by inspiring from the behavior type of Glowworm Swarm Optimization; and an application estimating the total population, square measurement and electricity quantity that was consumed by the chosen areas in a region was developed. The developed application works as a real-time and animated display. When all calculations are finished, the animation ends. Estimates also examined England as an example. The difference between the estimated value of the actual population of England is calculated as 1.7%. In the estimates for the values of the surface area of England with an error of 1.4%, the estimated values were very close to the actual values. Some other obtained estimation results are presented in the results section.en_US
dc.identifier.doi10.1007/s42835-020-00509-3
dc.identifier.endpage2360en_US
dc.identifier.issn1975-0102
dc.identifier.issn2093-7423
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85089559774en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage2345en_US
dc.identifier.urihttps://doi.org/10.1007/s42835-020-00509-3
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4329
dc.identifier.volume15en_US
dc.identifier.wosWOS:000561892400002en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Singapore Pte Ltden_US
dc.relation.ispartofJournal of Electrical Engineering & Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGlowworm swarm optimizationen_US
dc.subjectHeuristicsen_US
dc.subjectSatellite imagesen_US
dc.subjectSimulationen_US
dc.titleMaking Inferences About Settlements from Satellite Images Using Glowworm Swarm Optimizationen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu