dc.contributor.author | Javaid, Muhammad | en_US |
dc.contributor.author | Raheem, Abdul | en_US |
dc.contributor.author | Abbas, Mujhaid | en_US |
dc.contributor.author | Cao, Jinde | en_US |
dc.date.accessioned | 2020-11-03T13:27:36Z | |
dc.date.available | 2020-11-03T13:27:36Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Javaid, M., Raheem, A., Abbas, M. & Cao, J. (2019). M-polynomial method for topological indices of 3-layered probabilistic neural networks. TWMS Journal of Applied and Engineering Mathematics, 9(4), 864-875. | en_US |
dc.identifier.issn | 2146-1147 | en_US |
dc.identifier.issn | 2587-1013 | en_US |
dc.identifier.uri | http://belgelik.isikun.edu.tr/xmlui/handle/iubelgelik/2777 | |
dc.identifier.uri | http://jaem.isikun.edu.tr/web/index.php/archive/103-vol9no4/474 | |
dc.description.abstract | A molecular network can be uniquely identified by a number, polynomial or matrix. A topological index (TI) is a number that characterizes a molecular network completely which is used to predict the physical features of the certain changes such as bioactivities and chemical reactivities in the chemical compound. Javaid and Cao [Neural Comput. and Applic., 30(2018), 3869-3876] studied the first Zagreb index, second Zagreb index, general Randic index, and augmented Zagreb index for the 3-layered probabilistic neural networks (PNN). In this paper, we prove the M-polynomial of the 3-layered PNN and use it as a latest developed tool to compute the certain degree based TI’s. At the end, a comparison is also shown to find the better one among all the obtained results. | en_US |
dc.description.sponsorship | The authors would like to express their sincere gratitude to the anonymous referees for their insightful comments and valuable suggestions, which led to a number of improvements in the earlier version of this manuscript. For this work, the author Jinde Cao is jointly supported by the National Natural Science Foundation of China under grant nos. 61573096 and 61272530, and The Jiangsu Provincial Key Laboratory of Networked Collective Intelligence of China under grant no. BM2017002. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Işık University Press | en_US |
dc.relation.ispartof | TWMS Journal of Applied and Engineering Mathematics | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | M-polynomial | en_US |
dc.subject | Degree-based TI’s | en_US |
dc.subject | Networks | en_US |
dc.subject | Probabilistic neural network | en_US |
dc.title | M-polynomial method for topological indices of 3-layered probabilistic neural networks | en_US |
dc.type | Article | en_US |
dc.description.version | Publisher's Version | en_US |
dc.identifier.volume | 9 | |
dc.identifier.issue | 4 | |
dc.identifier.startpage | 864 | |
dc.identifier.endpage | 875 | |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Başka Kurum Yazarı | en_US |