Global Optimization of Near-Surface Potential Field Anomalies Through Metaheuristics

dc.contributor.author	Ekinci, Yunus Levent
dc.contributor.author	Balkaya, Caglayan
dc.contributor.author	Gokturkler, Gokhan
dc.date.accessioned	2021-12-16T09:06:50Z
dc.date.available	2021-12-16T09:06:50Z
dc.date.issued	2020
dc.identifier.isbn	978-3-030-28909-6; 978-3-030-28908-9
dc.identifier.issn	2364-9119
dc.identifier.uri	https://doi.org/10.1007/978-3-030-28909-6_7
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/9999
dc.description.abstract	In this study, global optimizations of the data sets obtained from potential field method applications including self-potential (SP), magnetic and gravity have been presented through particle swarm optimization (PSO), differential evolution algorithm (DEA
dc.language.iso	English
dc.publisher	Sprınger Internatıonal Publıshıng Ag
dc.source	Advances In Modelıng And Interpretatıon In Near Surface Geophysıcs
dc.title	Global Optimization of Near-Surface Potential Field Anomalies Through Metaheuristics
dc.type	Article; Book Chapter
dc.identifier.startpage	155
dc.identifier.endpage	188
dc.identifier.doi	10.1007/978-3-030-28909-6_7
dc.identifier.wos	WOS:000679916300008

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