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Wasim Ullah Khan
Researcher at Wuhan University
Publications - 22
Citations - 378
Wasim Ullah Khan is an academic researcher from Wuhan University. The author has contributed to research in topics: Nanofluid & Convection. The author has an hindex of 6, co-authored 22 publications receiving 132 citations. Previous affiliations of Wasim Ullah Khan include COMSATS Institute of Information Technology & University of Science and Technology of China.
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Journal ArticleDOI
Effects of Variable Transport Properties on Heat and Mass Transfer in MHD Bioconvective Nanofluid Rheology with Gyrotactic Microorganisms: Numerical Approach
Muhammad Awais,Saeed Ehsan Awan,Muhammad Asif Zahoor Raja,Nabeela Parveen,Wasim Ullah Khan,M.Y. Malik,Yigang He +6 more
TL;DR: In this paper, the authors used the Lie group analysis approach to compute the absolute invariants for the system of differential equations, which are solved numerically using Adams-Bashforth technique.
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Backtracking search integrated with sequential quadratic programming for nonlinear active noise control systems
TL;DR: Integrated strength of backtracking search algorithm (BSA) and sequential quadratic programming (SQP) is exploited for nonlinear active noise control (ANC) systems to demonstrate the worth of stochastic solvers BSA and BSA-S QP.
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Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path
TL;DR: In this article, a hybrid computational framework is developed for active noise control (ANC) systems using an evolutionary computing technique based on genetic algorithms (GAs) and interior-point method (IPM), following an integrated approach, GA-IPM.
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Cattaneo-christov heat flux model of 3D hall current involving biconvection nanofluidic flow with Darcy-Forchheimer law effect: Backpropagation neural networks approach
Muhammad Asif Zahoor Raja,Zeeshan Khan,Samina Zuhra,Naveed Ishtiaq Chaudhary,Wasim Ullah Khan,Yigang He,Saeed Islam,Muhammad Shoaib +7 more
TL;DR: In this paper, a backpropagated neural network (BNN) with Levenberg Marquardt technique (LMT) was used to estimate the flow rate dynamics, energy, nanofluid concentration and microorganism concentration profiles for different physical quantity based scenarios.
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Intelligent Backpropagation Networks with Bayesian Regularization for Mathematical Models of Environmental Economic Systems
Adiqa Kiani,Wasim Ullah Khan,Muhammad Asif Zahoor Raja,Yigang He,Zulqurnain Sabir,Muhammad Shoaib +5 more
TL;DR: In this investigation, AI-based intelligent backpropagation networks of Bayesian regularization (IBNs-BR) were exploited for the numerical treatment of mathematical models representing environmental economic systems (EESs) in the form of differential models representing their fundamental compartments or indicators for economic and environmental parameters.