Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651

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Author: search.filters.author.Sabir, ZulqurnainScopus Q: search.filters.scopusQuartile.Q3

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  • Article
    Citation - WoS: 8
    Citation - Scopus: 6
    Investigations of Non-Linear Induction Motor Model Using the Gudermannian Neural Networks
    (Vinca inst Nuclear Sci, 2022) Raja, Muhammad Asif Zahoor; Baleanu, Dumitru; Sadat, Rahma; Ali, Mohamed R.; Sabir, Zulqurnain
    This study aims to solve the non-linear fifth-order induction motor model (FO-IMM) using the Gudermannian neural networks (GNN) along with the optimization procedures of global search as a genetic algorithm together with the quick local search process as active-set technique (GNN-GA-AST). The GNN are executed to discretize the non-linear FO-IMM to prompt the fitness function in the procedure of mean square error. The exactness of the GNN-GA-AST is observed by comparing the obtained results with the reference results. The numerical performances of the stochastic GNN-GA-AST are provided to tackle three different variants based on the non-linear FO-IMM to authenticate the consistency, significance and efficacy of the designed stochastic GNN-GA-AST. Additionally, statistical illustrations are available to authenticate the precision, accuracy and convergence of the designed stochastic GNN-GA-AST.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 9
    A Hybrid Computing Approach To Design the Novel Second Order Singular Perturbed Delay Differential Lane-Emden Model
    (Iop Publishing Ltd, 2022) Baleanu, Dumitru; Raja, Muhammad Asif Zahoor; Hincal, Evren; Sabir, Zulqurnain
    In this study, the mathematical form of the second order perturbed singular delay differential system is presented. The comprehensive features using the singular-point, perturbed factor and pantograph term are provided together with the shape factor of the second order perturbed singular delay differential system. The novel model is simulated numerically through the artificial neural networks (ANNs) based on the global/local optimization procedures, i.e., genetic algorithm (GA) and sequential quadratic programming (SQP). An activation function is constructed by using the differential model based on the second order perturbed singular delay differential system. The optimization of fitness function is performed through the hybrid computing strength of the ANNs-GA-SQP to solve the second order perturbed singular delay differential system. The exactness, substantiation, and authentication of the novel system is observed to solve three different variants of the novel model. The convergence, robustness, correctness, and stability of the numerical approach is performed using the comparison procedures of the available exact solutions. For the reliability, the statistical performances with necessary processes are provided using the ANNs-GA-SQP.