Solution of novel multi-fractional multi-singular Lane–Emden model using the designed FMNEICS

Sabir, Zulqurnain; Raja, Muhammad Asif Zahoor; Guirao, Juan Luis García; Saeed, Tareq

doi:10.1007/s00521-021-06318-7

Cited by 20 publications

(7 citation statements)

References 93 publications

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“…GA works through the procedures of crossover, selection, elitism and mutation operators. In recent, GA is executed in lung cancer prognosis [35], wellhead backpressure control system [36], nonlinear circuits [37], heterogeneous mosquito release ecosystem [38], active noise control systems [39], multi-fractional multi-singular singular model [40], gas tungsten arc welding process [41], adjusting sensor acquisition frequency [42], multilayer piezoelectric transducer for broadband structures [43] and singular nonlinear system [44].…”

Section: Optimization: Ga-asamentioning

confidence: 99%

Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19

Sabir¹,

Alnahdi²,

Jeelani³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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The present investigations are associated with designing Morlet wavelet neural network (MWNN) for solving a class of susceptible, infected, treatment and recovered (SITR) fractal systems of COVID-19 propagation and control. The structure of an error function is accessible using the SITR differential form and its initial conditions. The optimization is performed using the MWNN together with the global as well as local search heuristics of genetic algorithm (GA) and active-set algorithm (ASA), i.e., MWNN-GA-ASA. The detail of each class of the SITR nonlinear COVID-19 system is also discussed. The obtained outcomes of the SITR system are compared with the Runge-Kutta results to check the perfection of the designed method. The statistical analysis is performed using different measures for 30 independent runs as well as 15 variables to authenticate the consistency of the proposed method. The plots of the absolute error, convergence analysis, histogram, performance measures, and boxplots are also provided to find the exactness, dependability and stability of the MWNN-GA-ASA.

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Section: Optimization: Ga-asamentioning

confidence: 99%

Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19

Sabir¹,

Alnahdi²,

Jeelani³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

Self Cite

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“…Recently, many systems that have been designed with the terminology of the Lane-Emden model. Few of them are the singular 2nd and 3rd pantograph model, 4th, 5th order and 6th kinds of functional singular systems, prediction, delay and pantograph form of the singular models [36][37][38][39][40][41][42][43][44] . Based on these applications, the authors are inspired to construct a novel SO-PSDDM.…”

Section: A Novel Design Of So-psddmmentioning

confidence: 99%

A neuro swarm procedure to solve the novel second order perturbed delay Lane-Emden model arising in astrophysics

Sabir

Saïd

Al‐Mdallal

et al. 2022

Sci Rep

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The current work provides a mathematical second order perturbed singular delay differential model (SO-PSDDM) by using the standard form of the Lane-Emden model. The inclusive structures based on the delay terms, singular-point and perturbation factor and shape forms of the SO-PSDDM are provided. The novel form of the SO-PSDDM is numerically solved by using the procedures of artificial neural networks (ANNs) along with the optimization measures based on the swarming procedures (PSO) and interior-point algorithm (IPA). An error function is optimized through the swarming PSO procedure along with the IPA to solve the SO-PSDDM. The precision, substantiation and validation are observed for three problems of the SO-PSDDM. The exactness of the novel SO-PSDDM is observed by comparing the obtained and exact solutions. The reliability, stability and convergence of the proposed stochastic algorithms are observed for 30 independent trials to solve the novel SO-PSDDM.

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“…The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing to solve the FO-HBV-DIS with the response of antibody immune. The stochastic numerical procedures have the competence and ability to solve the linear models as well as various stiff complex nonlinear systems [42][43][44][45][46][47][48][49][50]. These numerical performances of the integer order motivated the authors to present the numerical simulations of FO derivatives of nonlinear equations.…”

Section: Introductionmentioning

confidence: 99%

Numerical Procedure for Fractional HBV Infection with Impact of Antibody Immune

Noinang¹,

Sabir²,

Raja³

et al. 2023

Computers, Materials &Amp; Continua

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The current investigations are presented to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMBNNs. The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics, healthy hepatocytes (H), capsids (D), infected hepatocytes (I), free virus (V) and antibodies (W). The investigations for three different FO variants have been tested numerically to solve the nonlinear FO-HBV-DIS. The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing to solve the FO-HBV-DIS with the response of antibody immune. The numerical observations are achieved using the stochastic LMBNNs procedures for soling the FO-HBV-DIS with the response of antibody immune and comparison of the results is presented through the database Adams-Bashforth-Moulton approach. To authenticate the validity, competence, consistency, capability and exactness of the LMBNNs, the numerical presentations using the mean square error (MSE), error histograms (EHs), state transitions (STs), correlation and regression are accomplished.

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Solution of novel multi-fractional multi-singular Lane–Emden model using the designed FMNEICS

Cited by 20 publications

References 93 publications

Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19

Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19

A neuro swarm procedure to solve the novel second order perturbed delay Lane-Emden model arising in astrophysics

Numerical Procedure for Fractional HBV Infection with Impact of Antibody Immune

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