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Applications of neural networks for the novel designed of nonlinear fractional seventh order singular system

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Abstract

The purpose of this work is to design a novel nonlinear fractional seventh kind of singular (NSKS) Emden–Fowler model (EFM), i.e., NSKS-EFM together with its six categories. The novel design of NSKS-EFM is obtained with the use of typical EFM of the second kind. The shape factor and singular points detail is accessible for all six categories of the NSKS-EFM. The singular problems arise in the mathematical engineering problems, like as inverse models, creep or viscoelasticity problems. To check the correctness of the designed novel NSKS-EFM, three different cases of the first category will be solved by using the supervised neural networks (SNNs) together with the Levenberg–Marquardt backpropagation method (LMBM), i.e., SNNs-LMBM. A reference dataset based on the exact solutions with the SNNS-LMBM will be performed for each case of the novel NSKS-EFM. The obtained approximate solutions of all three cases of the first group based on the novel NSKS-EFM is available using the testing, training and verification procedures of the proposed NNs to summarize the mean square error (MSE) along with the LMBM. To check the efficiency, effectiveness, and correctness of the novel NSKS-EFM and the proposed SNNS-LMBM, the numerical investigations are obtainable using the comparative actions of MSE results, regression, error histograms and correlation.

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References

  1. Z. Shah et al., Design of neural network based intelligent computing for neumerical treatment of unsteady 3D flow of Eyring-Powell magneto-nanofluidic model. J. Market. Res. 9(6), 14372–14387 (2020)

    Google Scholar 

  2. M. Umar et al., A stochastic computational intelligent solver for numerical treatment of mosquito dispersal model in a heterogeneous environment. Eur. Phys. J. Plus 135(7), 1–23 (2020)

    Article  Google Scholar 

  3. I. Jadoon et al., Integrated meta-heuristics finite difference method for the dynamics of nonlinear unipolar electrohydrodynamic pump flow model. Appl. Soft Comput. 97, 106791 (2020)

    Article  Google Scholar 

  4. I. Jadoon et al., Design of evolutionary optimized finite difference based numerical computing for dust density model of nonlinear Van-der Pol Mathieu’s oscillatory systems. Math. Comput. Simul. 181, 444–470 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  5. A.H. Bukhari et al., Design of a hybrid NAR-RBFs neural network for nonlinear dusty plasma system. Alex. Eng. J. 59(5), 3325–3345 (2020)

    Article  Google Scholar 

  6. M. Umar et al., Stochastic numerical technique for solving HIV infection model of CD4\(+\) T cells. Eur. Phys. J. Plus 135(6), 403 (2020)

    Article  Google Scholar 

  7. K. Boubaker et al., Application of the BPES to Lane-Emden equations governing polytropic and isothermal gas spheres. New Astron. 17(6), 565–569 (2012)

    Article  ADS  Google Scholar 

  8. J.S. Wong, On the generalized Emden-Fowler equation. SIAM Rev. 17(2), 339–360 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  9. A.M. Wazwaz, Adomian decomposition method for a reliable treatment of the Emden-Fowler equation. Appl. Math. Comput. 161(2), 543–560 (2005)

    MathSciNet  MATH  Google Scholar 

  10. A. Taghavi et al., A solution to the Lane-Emden equation in the theory of stellar structure utilizing the Tau method. Math. Methods Appl. Sci. 36(10), 1240–1247 (2013)

    Article  MathSciNet  MATH  ADS  Google Scholar 

  11. Z. Sabir et al., Novel design of Morlet wavelet neural network for solving second order Lane-Emden equation. Math. Comput. Simul. 172, 1–14 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  12. W. Adel et al., Solving a new design of nonlinear second-order Lane-Emden pantograph delay differential model via Bernoulli collocation method. Eur Phys J Plus 135(6), 427 (2020)

    Article  Google Scholar 

  13. K. Nisar et al., Evolutionary Integrated Heuristic with Gudermannian Neural Networks for Second Kind of Lane-Emden Nonlinear Singular Models. Appl. Sci. 11(11), 4725 (2021)

    Article  Google Scholar 

  14. R. Singh et al., Haar wavelet collocation approach for Lane-Emden equations arising in mathematical physics and astrophysics. Eur. Phys. J. Plus 134(11), 548 (2019)

    Article  Google Scholar 

  15. F. Abbas et al., Approximate solutions to lane-emden equation for stellar configuration. Appl. Math. Inf. Sci. 13, 143–152 (2019)

    Article  MathSciNet  Google Scholar 

  16. S. Chandrasekhar, An Introduction to the Study of Stellar Structure (Dover Publications, New York, 1967)

    MATH  Google Scholar 

  17. T. Luo et al., Nonlinear asymptotic stability of the Lane-Emden solutions for the viscous gaseous star problem with degenerate density dependent viscosities. Commun. Math. Phys. 347(3), 657–702 (2016)

    Article  MathSciNet  MATH  ADS  Google Scholar 

  18. A.H. Bhrawy et al. An efficient collocation method for a class of boundary value problems arising in mathematical physics and geometry. in Abstract and Applied Analysis, vol. 2014. (Hindawi Publishing Corporation, 2014)

  19. J.A. Khan et al., Nature-inspired computing approach for solving non-linear singular Emden-Fowler problem arising in electromagnetic theory. Connect. Sci. 27(4), 377–396 (2015)

    Article  ADS  Google Scholar 

  20. J. Džurina, S.R. Grace, I. Jadlovská, T. Li, Oscillation criteria for second-order Emden-Fowler delay differential equations with a sublinear neutral term. Math. Nachr. 293, 1–13 (2020). https://doi.org/10.1002/mana.201800196

    Article  MathSciNet  MATH  Google Scholar 

  21. M. Dehghan et al., Solution of an integro-differential equation arising in oscillating magnetic fields using He’s homotopy perturbation method. Progr.Electromagnet. Res. 78, 361–376 (2008)

    Article  Google Scholar 

  22. J.I. Ramos, Linearization methods in classical and quantum mechanics. Comput. Phys. Commun. 153(2), 199–208 (2003)

    Article  MathSciNet  MATH  ADS  Google Scholar 

  23. V. Radulescu et al., Combined effects in nonlinear problems arising in the study of anisotropic continuous media. Nonlinear Anal. Theory Methods Appl. 75(3), 1524–1530 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  24. Z. Sabir et al., A neuro-swarming intelligence-based computing for second order singular periodic non-linear boundary value problems. Front. Phys. 8, 224 (2020)

    Article  Google Scholar 

  25. Z. Sabir et al., Design of stochastic numerical solver for the solution of singular three-point second-order boundary value problems. Neural Comput. Appl. 33(7), 2427–2443 (2021)

    Article  Google Scholar 

  26. Z. Sabir et al. Integrated intelligence of neuro-evolution with sequential quadratic programming for second-order Lane-Emden pantograph models. in Mathematics and Computers in Simulation (2021)

  27. Z. Sabir et al., Solution of novel multi-fractional multi-singular Lane-Emden model using the designed FMNEICS. Neural Comput. Appl. 33(24), 17287–17302 (2021)

    Article  Google Scholar 

  28. M.A. Abdelkawy et al., Numerical investigations of a new singular second-order nonlinear coupled functional Lane-Emden model. Open Phys. 18(1), 770–778 (2020)

    Article  Google Scholar 

  29. K. Parand et al., Rational Legendre approximation for solving some physical problems on semi-infinite intervals. Phys. Scr. 69(5), 353 (2004)

    Article  MATH  ADS  Google Scholar 

  30. Z. Sabir et al., Neuro-evolution computing for nonlinear multi-singular system of third order Emden-Fowler equation. Math. Comput. Simul. 185, 799–812 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  31. J.L. Guirao et al. Design and numerical solutions of a novel third-order nonlinear Emden–Fowler delay differential model. In: Mathematical Problems in Engineering (2020)

  32. Z. Sabir et al., Design of neuro-swarming-based heuristics to solve the third-order nonlinear multi-singular Emden-Fowler equation. Eur. Phys. J. Plus 135(6), 1–17 (2020)

    Google Scholar 

  33. N.T. Shawagfeh, Non-perturbative approximate solution for Lane-Emden equation. J. Math. Phys. 34(9), 4364–4369 (1993)

    Article  MathSciNet  MATH  ADS  Google Scholar 

  34. J.I. Ramos, Series approach to the Lane-Emden equation and comparison with the homotopy perturbation method. Chaos Solitons Fract. 38(2), 400–408 (2008)

    Article  MathSciNet  MATH  ADS  Google Scholar 

  35. A.K. Dizicheh, S. Salahshour, A. Ahmadian, D. Baleanu, A novel algorithm based on the Legendre wavelets spectral technique for solving the Lane–Emden equations. in Applied Numerical Mathematics (2020)

  36. U. Saeed, Haar Adomian method for the solution of fractional nonlinear Lane-Emden type equations arising in astrophysics. Taiwan. J. Math. 21(5), 1175–1192 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  37. M.S. Hashemi et al., Solving the Lane-Emden equation within a reproducing kernel method and group preserving scheme. Mathematics 5(4), 77 (2017)

    Article  MATH  Google Scholar 

  38. Z. Sabir et al. On a new model based on third-order nonlinear multi singular functional differential equations. in Mathematical Problems in Engineering (2020)

  39. Z. Sabir et al., Heuristic computing technique for numerical solutions of nonlinear fourth order Emden-Fowler equation. Math. Comput. Simul. 178, 534–548 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  40. Z. Sabir et al., FMNEICS: fractional Meyer neuro-evolution-based intelligent computing solver for doubly singular multi-fractional order Lane-Emden system. Comp. Appl. Math. 39, 303 (2020). https://doi.org/10.1007/s40314-020-01350-0

    Article  MathSciNet  MATH  Google Scholar 

  41. Z. Sabir et al., Integrated intelligent computing paradigm for nonlinear multi-singular third-order Emden-Fowler equation. Neural Comput. Appl. 33(8), 3417–3436 (2021)

    Article  Google Scholar 

  42. Z. Sabir et al., Meyer wavelet neural networks to solve a novel design of fractional order pantograph Lane-Emden differential model. Chaos Solitons Fract. 152, 111404 (2021)

  43. H. Günerhan, E. Çelik, Analytical and approximate solutions of fractional partial differential-algebraic equations. Appl. Math. Nonlinear Sci. 5(1), 109–120 (2020)

    Article  MathSciNet  Google Scholar 

  44. H.M. Baskonus et al., New complex hyperbolic structures to the lonngren-wave equation by using sine-gordon expansion method. Appl. Math. Nonlinear Sci. 4(1), 141–150 (2019)

    MathSciNet  Google Scholar 

  45. A. Yokuş, S. Gülbahar, Numerical solutions with linearization techniques of the fractional Harry Dym equation. Appl. Math. Nonlinear Sci. 4(1), 35–42 (2019)

    Article  MathSciNet  Google Scholar 

  46. J. Wu, J. Yuan, W. Gao, Analysis of fractional factor system for data transmission in SDN. Appl. Math. Nonlinear Sci. 4(1), 191–196 (2019)

    Article  MathSciNet  Google Scholar 

  47. H. Duru et al., New analytical solutions of conformable time fractional bad and good modified Boussinesq equations. Appl. Math. Nonlinear Sci. 5(1), 447–454 (2020)

  48. D.W. Brzeziński, Review of numerical methods for NumILPT with computational accuracy assessment for fractional calculus. Appl. Math. Nonlinear Sci. 3(2), 487–502 (2018)

    Article  MathSciNet  Google Scholar 

  49. E. Ilhan, I.O. Kıymaz, A generalization of truncated M-fractional derivative and applications to fractional differential equations. Appl. Math. Nonlinear Sci. 5(1), 171–188 (2020)

    Article  MathSciNet  Google Scholar 

  50. S.E. Awan et al., Numerical treatments to analyze the nonlinear radiative heat transfer in MHD nanofluid flow with solar energy. Arab. J. Sci. Eng. 45(6), 4975–4994 (2020)

    Article  Google Scholar 

  51. T. Sajid, et al. Impact of activation energy and temperature-dependent heat source/sink on maxwell–sutterby fluid. in Mathematical Problems in Engineering (2020)

  52. M. Modanli, A. Akgül, On Solutions of Fractional order Telegraph partial differential equation by Crank-Nicholson finite difference method. Appl. Math. Nonlinear Sci. 5(1), 163–170 (2020)

    Article  MathSciNet  Google Scholar 

  53. T. Sajid et al., Upshot of radiative rotating Prandtl fluid flow over a slippery surface embedded with variable species diffusivity and multiple convective boundary conditions. Heat Transf. 50(3), 2874–2894 (2021)

    Article  Google Scholar 

  54. T. Sajid et al., Impact of oxytactic microorganisms and variable species diffusivity on blood-gold Reiner-Philippoff nanofluid. Appl. Nanosci. 11(1), 321–333 (2021)

    Article  ADS  Google Scholar 

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Correspondence to Mohamed R. Ali.

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Sabir, Z., Raja, M.A.Z., Nguyen, T.G. et al. Applications of neural networks for the novel designed of nonlinear fractional seventh order singular system. Eur. Phys. J. Spec. Top. 231, 1831–1845 (2022). https://doi.org/10.1140/epjs/s11734-022-00457-1

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