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A New Stochastic Computing Paradigm for Nonlinear Painleve II Systems in Applications of Random Matrix Theory

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dc.contributor.author Raja, Muhammad Asif Zahoor
dc.contributor.author Shah, Zahoor
dc.contributor.author Manzar, Muhammad Anwaar
dc.contributor.author Ahmad, Iftikhar
dc.contributor.author Awais, Muhammad
dc.contributor.author Baleanu, Dumitru
dc.date.accessioned 2020-03-26T13:46:36Z
dc.date.available 2020-03-26T13:46:36Z
dc.date.issued 2018-07-10
dc.identifier.citation Raja, Muhammad Asif Zahoor...et al. (2018). "A new stochastic computing paradigm for nonlinear Painleve II systems in applications of random matrix theory", European Physical Journal Plus, Vol. 133, No. 7. tr_TR
dc.identifier.issn 2190-5444
dc.identifier.uri http://hdl.handle.net/20.500.12416/2756
dc.description.abstract The aim of the present work is to investigate the stochastic numerical solutions of nonlinear Painleve II systems arising from studies of two-dimensional Yang-Mills theory, growth processes through fluctuation formulas in statistical physics, soft-edge random matrix distributions using the strength of bioinspired heuristics through artificial neural networks (ANNs), genetic algorithm (GA)-based evolutionary computations and interior-point techniques (IPTs). A new mathematical modelling of the system is formulated through ANNs by defining an error function that exactly satisfies the initial conditions. The weights of ANN models optimized through a memetic computing approach that is based on a global search with GAs, and IPTs are used for an efficient local search. The designed scheme is substantiated through comparative analysis with a fully explicit Range-Kutta numerical procedure on nonlinear Painleve II systems by taking different magnitudes of forcing factors. The accuracy and convergence of the proposed scheme are validated through statistics performed on large numbers of simulations. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer Heidelberg tr_TR
dc.relation.isversionof 10.1140/epjp/i2018-12080-4 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Artifıcial Neural-Network tr_TR
dc.subject Interior-Point Algorithm tr_TR
dc.subject Boundary-Value-Problems tr_TR
dc.subject Differential-Equations tr_TR
dc.subject Computational Intelligence tr_TR
dc.subject Numerical Treatment tr_TR
dc.subject Dynamics; Design tr_TR
dc.subject Analyze tr_TR
dc.subject Heuristics tr_TR
dc.title A New Stochastic Computing Paradigm for Nonlinear Painleve II Systems in Applications of Random Matrix Theory tr_TR
dc.type article tr_TR
dc.relation.journal European Physical Journal Plus tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 133 tr_TR
dc.identifier.issue 7 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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