1,538
Views
4
CrossRef citations to date
0
Altmetric
Research Article

Applications of artificial neural network to solve the nonlinear COVID-19 mathematical model based on the dynamics of SIQ

, , , , &
Pages 874-884 | Received 05 Sep 2021, Accepted 27 Aug 2022, Published online: 19 Sep 2022

References

  • Umar M, et al. Stochastic numerical technique for solving HIV infection model of CD4+ T cells. Eur Phys J Plus. 2020;135(5):403.
  • Guerrero–Sánchez Y, et al. Solving a class of biological HIV infection model of latently infected cells using heuristic approach. Discrete Contin Dyn Syst-S. 2020;14(10):3611.
  • Umar M, et al. A novel study of Morlet neural networks to solve the nonlinear HIV infection system of latently infected cells. Results Phys. 2021;25:104235.
  • Umar M, et al. A stochastic numerical computing heuristic of SIR nonlinear model based on dengue fever. Results Phys. 2020;19:103585.
  • Lahiri A, Jha SS, Bhattacharya S. Effectiveness of preventive measures against COVID-19: A systematic review of In Silico modeling studies in indian context. Indian Journal of Public Health. 2020;64(6):156.
  • Hao X, Cheng S, Wu D, et al. Reconstruction of the full transmission dynamics of COVID-19 in Wuhan. Nature. 2020;584(7821):420–424.
  • Sánchez YG, et al. Design of a nonlinear SITR fractal model based on the dynamics of a novel coronavirus (COVID-19). Fractals. 2020;28(08):2040026.
  • Elsonbaty A, et al. Dynamical analysis of a novel discrete fractional SITRS model for COVID-19. Fractals. 2021;29(8):2140035.
  • Spiteri G, et al. First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020. Eurosurveillance. 2020;25(9):2000178.
  • Shim E. A note on epidemic models with infective immigrants and vaccination. Math Biosci Eng. 2006;3(3):557–566.
  • Rhodes T, et al. Mathematical models as public troubles in COVID-19 infection control: following the numbers. Health Sociol Rev. 2020;29(2):177–194.
  • Mustafa SK, et al. (2020). Brief review of the mathematical models for analyzing and forecasting transmission of COVID-19.
  • Benvenuto D, et al. Application of the ARIMA model on the COVID-2019 epidemic dataset. Data Brief. 2020;29:105340.
  • Bherwani H, Gupta A, Anjum S, et al. Exploring dependence of COVID-19 on environmental factors and spread prediction in India. npj Climate and Atmospheric Science. 2020;3(1):1-13.
  • Thompson RN. Epidemiological models are important tools for guiding COVID-19 interventions. BMC Med. 2020;18:1–4.
  • Nesteruk I. Estimates of the COVID-19 pandemic dynamics in Ukraine based on two data sets. medRxiv. 2021.
  • Libotte GB, Lobato FS, Platt GM, et al. Determination of an optimal control strategy for vaccine administration in COVID-19 pandemic treatment. Comput Methods Programs Biomed. 2020;196:105664.
  • Gumel AB, et al. A primer on using mathematics to understand COVID-19 dynamics: modeling, analysis and simulations. Infect Dis Model. 2021;6:148–168.
  • Sadiq IZ, Abubakar FS, Dan-Iya BI. Role of nanoparticles in tackling COVID-19 pandemic: a bio-nanomedical approach. J Taibah Univ Sci. 2021;15(1):198–207.
  • Ortenzi F, et al. A transdisciplinary analysis of COVID-19 in Italy: the most affected country in Europe. Int J Environ Res Public Health. 2020;17(24):9488.
  • Umar Y. Theoretical studies of the rotational and tautomeric states, electronic and spectroscopic properties of favipiravir and its structural analogues: a potential drug for the treatment of COVID-19. J Taibah Univ Sci. 2020;14(1):1613–1625.
  • Moore S, et al. Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study. Lancet Infect Dis. 2021;21(6):793–802.
  • Baba IA, Baba BA, Esmaili P. A mathematical model to study the effectiveness of some of the strategies adopted in curtailing the spread of COVID-19. Comput Math Methods Med. 2020;2020:6. doi:10.1155/2020/5248569
  • Anirudh AJIDM. Mathematical modeling and the transmission dynamics in predicting the COVID-19-what next in combating the pandemic. Infect Dis Model. 2020;5:366–374.
  • Zhang Z, et al. Dynamics of COVID-19 mathematical model with stochastic perturbation. Adv Differ Equ. 2020;2020(1):1–12.
  • Chen X, et al. Compliance and containment in social distancing: mathematical modeling of COVID-19 across townships. Int J Geogr Inf Sci. 2021;35(3):446–465.
  • Soumia M, Hanane Z, Benaissa M, et al. Towards potential inhibitors of COVID-19 main protease Mpro by virtual screening and molecular docking study. J. Taibah Univ. Sci.. 2020;14(1):1626–1636.
  • Ozturk T, Talo M, Yildirim EA, et al. Automated detection of COVID-19 cases using deep neural networks with X-ray images. Comput Biol Med. 2020;121:103792.
  • Niazkar HR, Niazkar M. Application of artificial neural networks to predict the COVID-19 outbreak. Glob Health Res Policy. 2020;5(1):1–11.
  • Saba AI, Elsheikh AH. Forecasting the prevalence of COVID-19 outbreak in Egypt using nonlinear autoregressive artificial neural networks. Process Saf Environ Prot. 2020;141:1–8.
  • Ozturka T, Talob M, Yildirimc EA, et al. Automated detection of COVID-19 cases using deep neural networks with X-ray images. Comput Biol Med. 2020;121(103792):10–1016.
  • Pham TD. A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks. Sci Rep. 2020;10(1):1–8.
  • Hamadneh NN, Khan WA, Ashraf W, et al. Artificial neural networks for prediction of COVID-19 in Saudi Arabia. Comput Mater Contin. 2021;66: 2787–2796.
  • Nisar K, et al. Evolutionary integrated heuristic with Gudermannian neural networks for second kind of Lane–Emden nonlinear singular models. Appl Sci. 2021;11(11):4725, doi:10.3390/app11114725.
  • Sabir Z, et al. Heuristic computing technique for numerical solutions of nonlinear fourth order Emden–Fowler equation. Math Comput Simul. 2020;178:534–548.
  • Nisar K, Sabir Z, Raja MAZ, et al. Design of Morlet wavelet neural network for solving a class of singular pantograph nonlinear differential models. IEEE Access. 2021;9:77845–77862.
  • Sabir Z, et al. Neuro-evolution computing for nonlinear multi-singular system of third order Emden–Fowler equation. Math Comput Simul. 2021;185:799–812.
  • Sabir Z, et al. Integrated intelligent computing paradigm for nonlinear multi-singular third-order Emden–Fowler equation. Neural Comput Appl. 2021;33(8):3417–3436.
  • Sabir Z, et al. Design of neuro-swarming-based heuristics to solve the third-order nonlinear multi-singular Emden–Fowler equation. Eur Phys J Plus. 2020;135(5):410.
  • Raja MAZ, et al. A new stochastic computing paradigm for the dynamics of nonlinear singular heat conduction model of the human head. Eur Phys J Plus. 2018;133(9):364.
  • Sabir Z, et al. Evolutionary computing for nonlinear singular boundary value problems using neural network, genetic algorithm and active-set algorithm. Eur Phys J Plus. 2021;136(2):1–19.
  • Raja MAZ, et al. Numerical solution of doubly singular nonlinear systems using neural networks-based integrated intelligent computing. Neural Comput Appl. 2019;31(3):793–812.
  • Sabir Z, et al. FMNEICS: fractional Meyer neuro-evolution-based intelligent computing solver for doubly singular multi-fractional order Lane–Emden system. Comput Appl Math. 2020;39(4):1–18.
  • Sabir Z, Wahab HA, Guirao JL. Integrated neuro-evolution heuristic with sequential quadratic programming for second-order prediction differential models. Numer Methods Partial Differ Equ. 2022;19(1):663–687.
  • Sabir Z, et al. Neuro-swarm intelligent computing to solve the second-order singular functional differential model. Eur Phys J Plus. 2020;135(6):1–19.
  • Sabir Z, et al. A novel design of fractional Meyer wavelet neural networks with application to the nonlinear singular fractional Lane-Emden systems. Alexandria Eng J. 2021;60(2):2641–2659.
  • Sabir Z. Stochastic numerical investigations for nonlinear three-species food chain system. Int J Biomath. 2022;15(04):2250005.
  • Sabir Z, Ali MR, Sadat R. Gudermannian neural networks using the optimization procedures of genetic algorithm and active set approach for the three-species food chain nonlinear model. J Ambient Intell Humaniz Comput. 2022: 1–10. doi:10.1007/s12652-021-03638-3
  • Ahmad SI, et al. A new heuristic computational solver for nonlinear singular Thomas–Fermi system using evolutionary optimized cubic splines. Eur Phys J Plus. 2020;135(1):1–29.
  • Bukhari AH, et al. Design of a hybrid NAR-RBFs neural network for nonlinear dusty plasma system. Alexandria Eng J. 2020;59(5):3325–3345.
  • Mehmood A, et al. Integrated computational intelligent paradigm for nonlinear electric circuit models using neural networks, genetic algorithms and sequential quadratic programming. Neural Comput Appl. 2020;32(14):10337–10357.
  • Sabir Z. Neuron analysis through the swarming procedures for the singular two-point boundary value problems arising in the theory of thermal explosion. Eur Phys J Plus. 2022;137(5):638.
  • Bukhari AH, et al. Fractional neuro-sequential ARFIMA-LSTM for financial market forecasting. IEEE Access. 2020;8:71326–71338.
  • Kiani AK, et al. Intelligent backpropagation networks with Bayesian regularization for mathematical models of environmental economic systems. Sustainability. 2021;13(17):9537.
  • Umar M, et al. Integrated neuro-swarm heuristic with interior-point for nonlinear SITR model for dynamics of novel COVID-19. Alexandria Eng J. 2021;60(3):2811–2824.
  • Umar M, et al. A stochastic intelligent computing with neuro-evolution heuristics for nonlinear SITR system of novel COVID-19 dynamics. Symmetry (Basel). 2020;12(10):1628.
  • Cheema TN, et al. Intelligent computing with Levenberg–Marquardt artificial neural networks for nonlinear system of COVID-19 epidemic model for future generation disease control. Eur Phys J Plus. 2020;135(11):1–35.
  • Botmart T, Sabir Z, Javeed S, et al. Artificial neural network-based heuristic to solve COVID-19 model including government strategies and individual responses. Inform Med Unlocked. 2022;33:101028. doi:10.1016/j.imu.2022.101028.
  • Bhadauria AS, et al. A SIQ mathematical model on COVID-19 investigating the lockdown effect. Infect Dis Model. 2021;6:244–257.
  • Iqbal M, Seadawy AR, Khalil OH, et al. Propagation of long internal waves in density stratified ocean for the (2 + 1)-dimensional nonlinear Nizhnik-Novikov-Vesselov dynamical equation. Results Phys. 2020;16:102838.
  • Baskonus HM, Bulut H. New wave behaviors of the system of equations for the ion sound and Langmuir waves. Waves in Random and Complex Media. 2016;26(4):613–625.
  • Iqbal M, Seadawy AR. Instability of modulation wave train and disturbance of time period in slightly stable media for unstable nonlinear Schrödinger dynamical equation. Mod Phys Lett B. 2020;34(supp01):2150010.
  • Seadawy AR, Iqbal M. Propagation of the nonlinear damped Korteweg-de Vries equation in an unmagnetized collisional dusty plasma via analytical mathematical methods. Math Methods Appl Sci. 2021;44(1):737–748.
  • Awais M, et al. Intelligent numerical computing paradigm for heat transfer effects in a Bodewadt flow. Surf Interfaces. 2021;26:101321.
  • Awan SE, et al. Intelligent Bayesian regularization networks for bio-convective nanofluid flow model involving gyro-tactic organisms with viscous dissipation, stratification and heat immersion. Eng Appl Comput Fluid Mech. 2021;15(1):1508–1530.
  • Shoaib M, et al. Soft computing paradigm for Ferrofluid by exponentially stretched surface in the presence of magnetic dipole and heat transfer. Alexandria Eng J. 2022;61(2):1607–1623.
  • Naz S, et al. Neuro-intelligent networks for Bouc–Wen hysteresis model for piezostage actuator. Eur Phys J Plus. 2021;136(4):1–20.
  • Elzeki OM, Shams M, Sarhan S, et al. COVID-19: a new deep learning computer-aided model for classification. PeerJ Comput Sci. 2021;7:e358.
  • Elzeki OM, Abd Elfattah M, Salem H, et al. A novel perceptual two layer image fusion using deep learning for imbalanced COVID-19 dataset. PeerJ Computer Science. 2021;7:e364.
  • Shams MY, Elzeki OM, Abouelmagd LM, et al. HANA: a healthy artificial nutrition analysis model during COVID-19 pandemic. Comput Biol Med. 2021;135:104606.