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dc.contributor.authorUcan, ON
dc.contributor.authorOzkan, T
dc.contributor.authorOzmen, A
dc.contributor.authorAlbora, AM
dc.date.accessioned2021-03-03T13:03:39Z
dc.date.available2021-03-03T13:03:39Z
dc.date.issued2001
dc.identifier.citationAlbora A., Ucan O., Ozmen A., Ozkan T., "Separation of Bouguer anomaly map using cellular neural network", JOURNAL OF APPLIED GEOPHYSICS, cilt.46, sa.2, ss.129-142, 2001
dc.identifier.issn0926-9851
dc.identifier.otherav_31c64920-dfab-4d48-9b1f-87c2c08cafa2
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/37827
dc.identifier.urihttps://doi.org/10.1016/s0926-9851(01)00033-7
dc.description.abstractIn this paper, a modern image-processing technique, the Cellular Neural Network (CNN) has been firstly applied to Bouguer anomaly map of synthetic examples and then to data from the Sivas-Divrigi Akdag region. CNN is an analog parallel computing paradigm defined in space and characterized by the locality of connections between processing neurons. The behaviour of the CNN is defined by two template matrices and a template vector. We have optimised the weight coefficients of these templates using the Recurrent Perceptron Learning Algorithm (RPLA). After testing CNN performance on synthetic examples, the CNN approach has been applied to the Bouguer anomaly of Sivas-Divrigi Akdag region and the results match drilling logs done by Mineral Research and Exploration (MTA). (C) 2001 Published by Elsevier Science B.V.
dc.language.isoeng
dc.subjectMaden Mühendisliği ve Teknolojisi
dc.subjectMühendislik ve Teknoloji
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectJeoloji Mühendisliği
dc.subjectJEOLOJİ
dc.subjectMühendislik
dc.subjectMADEN VE MİNERAL İŞLEM
dc.subjectTemel Bilimler (SCI)
dc.subjectYerbilimleri
dc.subjectYER BİLİMİ, MULTİDİSİPLİNER
dc.titleSeparation of Bouguer anomaly map using cellular neural network
dc.typeMakale
dc.relation.journalJOURNAL OF APPLIED GEOPHYSICS
dc.contributor.department, ,
dc.identifier.volume46
dc.identifier.issue2
dc.identifier.startpage129
dc.identifier.endpage142
dc.contributor.firstauthorID127710


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