Evolutionary optimized Padé approximation scheme for analysis of covid-19 model with crowding effect

Zeb, 2020, Mathematical model for coronavirus disease 2019 (Covid-19) containing isolation class, Biomed Res Int, 10, 1 Riyapan, 2021, A mathematical model of covid-19 pandemic: a case study of bangkok, thailand, Comput Math Methods Med, 2021, 1, 10.1155/2021/6664483 Oud, 2021, A fractional-order mathematical model for covid-19 dynamics with quarantine, isolation, and environmental viral load, Advan Difference Equations, 2021, 1 Shaikh, 2021, A mathematical model of covid-19 using fractional derivative: outbreak in india with dynamics of transmission and control, Advan Difference Equations, 2020, 1 Ahmed, 2021, A mathematical model of coronavirus disease (Covid-19) containing asymptomatic and symptomatic classes, Results in Physics, 2021, 1 Ullah, 2020, Modelling the impact of non-pharmaceutical interventions on the dynamics of novel coronavirus with optimal control analysis with a case study, Chaos, Solitons Fractals, 2020, 1 Peter, 2021, A new mathematical model of covid-19 using real data from pakistan, Results in Phy, 2021, 1 Nazir, 2021, Study of covid-19 mathematical model of fractional order via modified euler method, Alexandria Engineering Journal, 60, 5287, 10.1016/j.aej.2021.04.032 Kyrychko, 2020, Mathematical modelling of the dynamics and containment of covid-19 in ukraine, Sci Rep, 10, 1, 10.1038/s41598-020-76710-1 Khoshnaw, 2020, Mathematical modelling for coronavirus disease (Covid-19) in predicting future behaviours and sensitivity analysis, Math Model Nat Phenom, 10, 1 Sasmita, 2020, Optimal control on a mathematical model to pattern the progression of coronavirus disease 2019 (Covid-19) in indonesia, Global Health Research and Policy, 5, 1, 10.1186/s41256-020-00163-2 Tiwari, 2020, Mathematical modelling based study and prediction of covid-19 epidemic dissemination under the impact of lockdown in india, medRxiv, 6, 1 Wang, 2021, Mathematical modelling of transmission dynamics of covid-19, Big Data and Information Analytics, 6, 12, 10.3934/bdia.2021002 Baek, 2020, A mathematical model of covid-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies, PLoS One, 15, 1, 10.1371/journal.pone.0241169 Santaella-Tenorio, 2020, Mathematical model and covid-19 modelos matemáticos y el covid-19, Colomb. Med., 51, 1, 10.25100/cm.v51i2.4272 Peter, 2020, Analysis and dynamics of fractional-order mathematical model of covid-19 in nigeria using atangana-baleanu operator, Computers, Materials and Continua, 66, 1 Moyles, 2020, Cost and social distancing dynamics in a mathematical model of covid-19 with application to ontario, canada, medRxiv, 15, 1 Krivorot'ko, 2020, Mathematical modelling and forecasting of covid-19 in moscow and novosibirsk region, Numer Anal Appl, 13, 332, 10.1134/S1995423920040047 Harjule, 2021, Mathematical models to predict covid-19 outbreak: an interim review, J Interdiscip Math, 15, 1 Kim, 2020, Mathematical model of covid-19 transmission dynamics in south korea: the impacts of travel restrictions, social distancing, and early detection, Processes, 8, 1, 10.3390/pr8101304 Diaz, 2021, Analysis of a nonstandardnonstandard computer method to simulate a nonlinear stochastic epidemiological model of coronavirus-like diseases, Comput Methods Programs Biomed, 204, 1 Raza, 2021, An analysis of a nonlinear susceptible-exposed-infected-quarantine-recovered pandemic model of a novel coronavirus with delay effect, Results in Physics, 21, 01, 10.1016/j.rinp.2020.103771 Zamir, 2021, Threshold conditions for global stability of disease free, Results in Physics, 21, 10.1016/j.rinp.2020.103784 Gupta, 2021, An emotion care model using multimodal textual analysis on COVID-19, Chaos, Solitons Fractals, 144, 10.1016/j.chaos.2021.110708 Saha, 2021, GraphCovidNet: a graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest, Sci Rep, 11, 1 Ahmad, 2020, Fuzzy fractional-order model of the novel coronavirus, Adv Difference Equat, 2020, 1 Ahmad, 2021, Numerical simulation and stability analysis of a novel reaction-diffusion covid-19 model, Nonlinear Dyn, 23, 01 Ghorui, 2021, Identification of dominant risk factor involved in spread of COVID-19 using hesitant fuzzy mcdm methodology, Results in physics, 21, 10.1016/j.rinp.2020.103811 Shariq, 2021, A secure and reliable rfid authentication protocol using digital schnorr cryptosystem for iot-enabled healthcare in COVID-19 scenario, Sustainable Cities and Society, 75, 10.1016/j.scs.2021.103354 Mateescu, 2006, On the application of genetic algorithms to differential equations, Romanian J Economic Forecasting, 2, 5 Lee, 2006, Method of bilaterally bounded to solution blasius equation using particle swarm optimization, Appl Math Comput, 179, 779 Babaei, 2013, A general approach to approximate solutions of nonlinear differential equations using particle swarm optimization, Appl Soft Comput, 13, 3354, 10.1016/j.asoc.2013.02.005 Karr, 2003, A self-tuning evolutionary algorithm applied to an inverse partial differential equation, Appl Intelligence, 19, 147, 10.1023/A:1026097605403 Cao, 2000, Evolutionary modelling of systems of ordinary differential equations with genetic programming, Genetic Programming and Evolvable Machines, 1, 309, 10.1023/A:1010013106294 Mastorakis, 2006, Unstable ordinary differential equations: solution via genetic algorithms and the method of nelder-mead, WSEAS Trans Math, 5, 1276 Pageant, 2014, Solving partial differential equations using a new differential evolution algorithm, Math Probl Eng, 2014, 10 Ali, 2018, Numerical treatment of nonlinear model of virus propagation in computer networks: an innovative evolutionary padé approximation scheme, Adv Difference Equations, 2018, 10.1186/s13662-018-1672-1 Nisar, 2021, Hybrid evolutionary padé approximation approach for numerical treatment of nonlinear partial differential equations, Alexandria Engineering J, 60, 4411, 10.1016/j.aej.2021.03.030 Baker, 1975 Baker G.A., Morris P.G., Padé approximants, Addison-Wesley, 1981. Padѐ, 1892, Sur la representation approchѐe d'une fonction par des fractions rationnelles, Annales Scientifiques De l'École Normale Supérieure, 9, 1 Leal, 2013, Application of series method with padé and laplace-padé re-summation methods to solve a model for the evolution of smoking habit in spain, Computat Appl Mathem, 33, 1 Rashidi, 2010, Using differential transform method and padé approximant for solving mhd flow in a laminar liquid film from a horizontal stretching surface, Math Probl Eng, 2010, 10.1155/2010/491319 Guerrero, 2013, Solving a model for the evolution of smoking habit in spain with homotopy analysis method, Nonlinear Analysis: Real-World Application, 14, 549, 10.1016/j.nonrwa.2012.07.015 Wang, 2011, Adomian decomposition and padé approximate for solving differential-difference equation, Appl Math Comput, 218, 1371 Yang, 2008 Rao, 2011, Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems, Comput-Aided Des, 43, 303, 10.1016/j.cad.2010.12.015 Kennedy, 1995, Particle swarm optimization, 1942 Storn, 1997, Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces, J Global Optim, 11, 341, 10.1023/A:1008202821328 Goldberg, 1989 Luqman, 2019, Targeted showering optimization: training irrigation tools to solve crop planning problems, Pak J Agricult Sci, 56, 225 Ali, 2019, Controlled showering optimization algorithm: an intelligent tool for decision making in global optimization, Comput Math Organ Theory, 25, 132, 10.1007/s10588-019-09293-6 Eskandar, 2012, Water cycle algorithm – a novel metaheuristic optimization method for solving constrained engineering optimization problems, Comput Struct, 110–111, 151, 10.1016/j.compstruc.2012.07.010 Alatas, 2017, Sports inspired computational intelligence algorithms for global optimization, Artif Intell Rev Karaboga, 2007, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, J Global Optim, 39, 459, 10.1007/s10898-007-9149-x Mirjalili, 2014, Grey wolf optimizer, Adv Eng Software, 69, 46, 10.1016/j.advengsoft.2013.12.007 Alexandros, 2017, Nature-inspired optimization algorithms related to physical phenomena and laws of science: a survey, Intern J Artif Intell Tools, 26, 10.1142/S0218213017500221 Wolpert, 1997, No free lunch theorems for optimization, IEEE Trans Evol Comput, 1, 67, 10.1109/4235.585893 2005, 479 Ali, 2017, Low cost-efficient remedial strategy for stagnated nelder-mead simplex method, Pak J Sci, 69, 119 Nelder, 1965, A simple method for function minimization, Comput J, 7, 308, 10.1093/comjnl/7.4.308 Mickens, 2005, A fundamental principle for constructing nonstandardnonstandard finite difference schemes for differential equations, J Differ Equations Appl, 11, 645, 10.1080/10236190412331334527