Intelligent computing to solve fifth-order boundary value problem arising in induction motor models

Ahmad, Iftikhar; Ahmad, Fayyaz; Raja, Muhammad Asif Zahoor; Ilyas, Hira; Anwar, Nabeela; Azad, Zarqa

doi:10.1007/s00521-016-2547-6

Cited by 64 publications

(9 citation statements)

References 19 publications

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“…In Future, such equations which may have infinite domains or difficult to solve by other numerical techniques can be solved by Sinc collocation method, quite successfully, moreover, this technique provides more accurate and efficient solutions for the higher order equations [47] , [48] , also can applied on the system of equations [49] , [50] , [51] .…”

Section: Discussionmentioning

confidence: 99%

Numerical computing approach for solving Hunter-Saxton equation arising in liquid crystal model through sinc collocation method

Ahmad

Ilyas

Kutlu

et al. 2021

Heliyon

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In this study, numerical treatment of liquid crystal model described through Hunter-Saxton equation (HSE) has been presented by sinc collocation technique through theta weighted scheme due to its enormous applications including, defects, phase diagrams, self-assembly, rheology, phase transitions, interfaces, and integrated biological applications in mesophase materials and processes. Sinc functions provide the procedure for function approximation over all types of domains containing singularities, semi-infinite or infinite domains. Sinc functions have been used to reduce HSE into an algebraic system of equations that makes the solution quite superficial. These algebraic equations have been interpreted as matrices. This projected that sinc collocation technique is considerably efficacious on computational ground for higher accuracy and convergence of numerical solutions. Stability analysis of the proposed technique has ensured the accuracy and reliability of the method, moreover, as the stability parameter satisfied the condition the proposed solution of the problem converges. The solution of the HSE is presented through graphical figures and tables for different cases that are constructed on various values of and collocation points. The accuracy and efficiency of the proposed technique is analyzed on the basis of absolute errors.

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Section: Discussionmentioning

confidence: 99%

Numerical computing approach for solving Hunter-Saxton equation arising in liquid crystal model through sinc collocation method

Ahmad

Ilyas

Kutlu

et al. 2021

Heliyon

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“… Numerical results for the laminar boundary-layer over a wedge are are in close approximation with already published work. In future, one may investigate modern soft computing based numerical solvers for the solution of hydromagnetic Falkner-Skan fluidic systems [30][31][32][33].…”

Section: Discussionmentioning

confidence: 99%

Hydromagnetic Falkner-Skan fluid rheology with heat transfer properties

et al. 2020

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Original scientific paper https://doi.org/10.2298/TSCI180509312A This article addresses the effects of heat transfer on magnetohydrodynamic Falkner-Skan wedge flow of a Jeffery fluid. The continuity, momentum and energy balance equations yield the relevant PDE which are transforms to ODE by exploitation of similarity variables. Strength of optimal homotopy series solutions is practiced to solved analytically the transformed ODE model of hydromagnetic Falkner-Skan fluid rheology with heat transfer scenarios. The graphical and numerical illustrations of the result are presented for different interesting flow parameters. Numerical values of Nusselt number are tabulated. It is observed that for the Falkner-Skan rheology, the applied magnetic field acts as a controlling agnet which controls the fluids velocity up to the desired value whereas Debrorah number enhances the fluid velocity.

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“…In these intelligence computing schemes, the strength of artificial neural networks (ANN) and optimization with local and global search algorithms are exploited [ 28 ]. The spectrum of ANN modeling is spreading extensively in various real-life studies such as electromagnetism [ 29 ], nonlinear optics [ 30 ], nanotechnology [ 31 ], bioinformatics [ 32 ], mathematical equations [ 33 ], meteorology [ 34 ], fluid dynamics [ 35 ], thermodynamics [ 36 ], rotating electrical machine [ 37 ], electric motors [ 38 ], atomic physics [ 39 ], plasma physics [ 40 ] and astrophysics [ 41 ]. ANNs show outstanding and significant performance in real-life applications and emerged as one of the dominating models [ 42 ].…”

Section: Introductionmentioning

confidence: 99%

Design of Nonlinear Autoregressive Exogenous Model Based Intelligence Computing for Efficient State Estimation of Underwater Passive Target

Ali

Khan

Raja

et al. 2021

Entropy

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In this study, an intelligent computing paradigm built on a nonlinear autoregressive exogenous (NARX) feedback neural network model with the strength of deep learning is presented for accurate state estimation of an underwater passive target. In underwater scenarios, real-time motion parameters of passive objects are usually extracted with nonlinear filtering techniques. In filtering algorithms, nonlinear passive measurements are associated with linear kinetics of the target, governing by state space methodology. To improve tracking accuracy, effective feature estimation and minimizing position error of dynamic passive objects, the strength of NARX based supervised learning is exploited. Dynamic artificial neural networks, which contain tapped delay lines, are suitable for predicting the future state of the underwater passive object. Neural networks-based intelligence computing is effectively applied for estimating the real-time actual state of a passive moving object, which follows a semi-curved path. Performance analysis of NARX based neural networks is evaluated for six different scenarios of standard deviation of white Gaussian measurement noise by following bearings only tracking phenomena. Root mean square error between estimated and real position of the passive target in rectangular coordinates is computed for evaluating the worth of the proposed NARX feedback neural network scheme. The Monte Carlo simulations are conducted and the results certify the capability of the intelligence computing over conventional nonlinear filtering algorithms such as spherical radial cubature Kalman filter and unscented Kalman filter for given state estimation model.

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Intelligent computing to solve fifth-order boundary value problem arising in induction motor models

Cited by 64 publications

References 19 publications

Numerical computing approach for solving Hunter-Saxton equation arising in liquid crystal model through sinc collocation method

Numerical computing approach for solving Hunter-Saxton equation arising in liquid crystal model through sinc collocation method

Hydromagnetic Falkner-Skan fluid rheology with heat transfer properties

Design of Nonlinear Autoregressive Exogenous Model Based Intelligence Computing for Efficient State Estimation of Underwater Passive Target

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