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Estimation of cross sections for molecule-cluster interactions by using artificial neural networks

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dc.contributor.author Böyükata, Mustafa
dc.contributor.author Koçyiğit, Yücel
dc.contributor.author Güvenç, Büşra
dc.date.accessioned 2016-03-31T07:49:05Z
dc.date.available 2016-03-31T07:49:05Z
dc.date.issued 2006-09
dc.identifier.citation Böyükata, M., Koçyiğit, Y., Güvenç, Z.B. (2006). Estimation of cross sections for molecule-cluster interactions by using artificial neural networks. Brazilian Journal of Physics, 36(3A), 730-735 tr_TR
dc.identifier.issn 0103-9733
dc.identifier.uri http://hdl.handle.net/20.500.12416/786
dc.description.abstract The cross sections Of D(2) (v,j) + Ni(n) (T), n = 19 and 20, collision systems have been estimated by using Artificial Neural Networks (ANNs). For training, previously determined cross section values via molecular dynamics simulation have been used. The performance of the ANNs for predicting any quantities in molecule-cluster interaction has been investigated. Effects of the temperature of the clusters and the rovibrational states of the molecule are analyzed. The results are in good agreement with previous studies. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer tr_TR
dc.rights info:eu-repo/semantics/closedAccess
dc.subject Artificial Neural Networks tr_TR
dc.subject Molecular Dynamics tr_TR
dc.subject Clusters tr_TR
dc.subject Reactivity tr_TR
dc.title Estimation of cross sections for molecule-cluster interactions by using artificial neural networks tr_TR
dc.type article tr_TR
dc.relation.journal Brazilian Journal of Physics tr_TR
dc.contributor.authorID 120207 tr_TR
dc.contributor.authorID 53469 tr_TR
dc.identifier.volume 36 tr_TR
dc.identifier.issue 3A tr_TR
dc.identifier.startpage 730 tr_TR
dc.identifier.endpage 735 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği tr_TR


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