Browsing by Author "Ahmad, Iftikhar"

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Citation Count: 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.
A New Stochastic Computing Paradigm for Nonlinear Painleve II Systems in Applications of Random Matrix Theory
(Springer Heidelberg, 2018) Raja, Muhammad Asif Zahoor; Shah, Zahoor; Manzar, Muhammad Anwaar; Ahmad, Iftikhar; Awais, Muhammad; Baleanu, Dumitru; 56389
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.
Citation Count: Ahmad, Iftikhar...et al. (2019). "Design of computational intelligent procedure for thermal analysis of porous fin model", Chinese Journal of Physics, Vol. 59, pp. 641-655.
Design of computational intelligent procedure for thermal analysis of porous fin model
(Elsevier, 2019) Ahmad, Iftikhar; Zahid, Hina; Ahmad, Fayyaz; Raja, Muhammad Asif Zahoor; Baleanu, Dumitru; 56389
The importance of rectangular porous fins for the transformation of heat through the system is well-recognized to analyze the physical characteristics of material in practical applications. In this study, a neuro-computing based stochastic numerical paradigm has been designed to study the dynamics of temperature distribution in porous fin model by exploiting the strength of artificial neural network (ANN) modeling integrated with global search exploration with genetic algorithms (GAs) and efficient local search with interior-point technique (IPT). The governing porous fin equation is transformed into an equivalent nonlinear second order ordinary differential equation. Effect of heat on rectangular type fin with thermal conductivity and temperature dependent internal heat generation is measured through stochastic solver based on ANN optimized with GA-IPT in case of two different materials, Silicon nitride Si3N4 and Aluminium Al. The proposed technique ANN-GA-IPT has been applied on transformed equation for multi-times and the accuracy, convergence and robustness of designed model has been validated by analysis of variance test.