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Design of Gudermannian Neuroswarming to solve the singular Emden-Fowler nonlinear model numerically

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dc.contributor.author Sabir, Zulqurnain
dc.contributor.author Raja, Muhammad Asif Zahoor
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Cengiz, Korhan
dc.contributor.author Shoaib, Muhammad
dc.date.accessioned 2022-03-31T13:21:45Z
dc.date.available 2022-03-31T13:21:45Z
dc.date.issued 2021-12
dc.identifier.citation Sabir, Zulqurnain...et al. (2021). "Design of Gudermannian Neuroswarming to solve the singular Emden-Fowler nonlinear model numerically", Nonlinear Dynamics, Vol. 106, No. 4, pp. 3199-3214. tr_TR
dc.identifier.uri http://hdl.handle.net/20.500.12416/5236
dc.description.abstract The current investigation is related to the design of novel integrated neuroswarming heuristic paradigm using Gudermannian artificial neural networks (GANNs) optimized with particle swarm optimization (PSO) aid with active-set (AS) algorithm, i.e., GANN-PSOAS, for solving the nonlinear third-order Emden-Fowler model (NTO-EFM) involving single as well as multiple singularities. The Gudermannian activation function is exploited to construct the GANNs-based differential mapping for NTO-EFMs, and these networks are arbitrary integrated to formulate the fitness function of the system. An objective function is optimized using hybrid heuristics of PSO with AS, i.e., PSOAS, for finding the weights of GANN. The correctness, effectiveness and robustness of the designed GANN-PSOAS are verified through comparison with the exact solutions on three problems of NTO-EFMs. The assessments on statistical observations demonstrate the performance on different measures for the accuracy, consistency and stability of the proposed GANN-PSOAS solver. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1007/s11071-021-06901-6 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Gudermannian Function tr_TR
dc.subject Particle Swarm Optimization tr_TR
dc.subject Emden–Fowler tr_TR
dc.subject Active-Set Scheme tr_TR
dc.subject Statistical Analysis tr_TR
dc.title Design of Gudermannian Neuroswarming to solve the singular Emden-Fowler nonlinear model numerically tr_TR
dc.type article tr_TR
dc.relation.journal Nonlinear Dynamics tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 106 tr_TR
dc.identifier.issue 4 tr_TR
dc.identifier.startpage 3199 tr_TR
dc.identifier.endpage 3214 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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