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10.7717/peerj.10019 http://scihub22266oqcxt.onion/10.7717/peerj.10019 33005495!7513748!33005495     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PeerJ 2020 ; 8 (ä): e10019 Nephropedia Template TP {{tp|p=33005495|t=2020. Theta-SEIHRD mathematical model of Covid19-stability analysis using fast-slow decomposition |pdf=|usr=}}{{33005495}} gab.com Text Theta-SEIHRD mathematical model of Covid19-stability analysis using fast-slow decomposition JO: PeerJ http://www.kidney.de/pget.php?&tw=1&pmid=33005495 #FOAvip In general, a mathematical model that contains many linear/nonlinear differential equations, describing a phenomenon, does not have an explicit hierarchy of system variables. That is, the identification of the fast variables and the slow variables of the system is not explicitly clear. The decomposition of a system into fast and slow subsystems is usually based on intuitive ideas and knowledge of the mathematical model being investigated. In this study, we apply the singular perturbed vector field (SPVF) method to the COVID-19 mathematical model of to expose the hierarchy of the model. This decomposition enables us to rewrite the model in new coordinates in the form of fast and slow subsystems and, hence, to investigate only the fast subsystem with different asymptotic methods. In addition, this decomposition enables us to investigate the stability analysis of the model, which is important in case of COVID-19. We found the stable equilibrium points of the mathematical model and compared the results of the model with those reported by the Chinese authorities and found a fit of approximately 96 percent. Twit Text FOAVip Theta-SEIHRD mathematical model of Covid19-stability analysis using fast-slow decomposition ????PeerJ http://www.kidney.de/pget.php?&tw=1&pmid=33005495 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33005495 #FOAvip English Wikipedia <ref>{{Cite pmid|33005495}}</ref> Theta-SEIHRD mathematical model of Covid19-stability analysis using fast-slow decomposition #MMPMID33005495 Nave O; Hartuv I; Shemesh U PeerJ 2020[]; 8 (ä): e10019 PMID33005495show ga In general, a mathematical model that contains many linear/nonlinear differential equations, describing a phenomenon, does not have an explicit hierarchy of system variables. That is, the identification of the fast variables and the slow variables of the system is not explicitly clear. The decomposition of a system into fast and slow subsystems is usually based on intuitive ideas and knowledge of the mathematical model being investigated. In this study, we apply the singular perturbed vector field (SPVF) method to the COVID-19 mathematical model of to expose the hierarchy of the model. This decomposition enables us to rewrite the model in new coordinates in the form of fast and slow subsystems and, hence, to investigate only the fast subsystem with different asymptotic methods. In addition, this decomposition enables us to investigate the stability analysis of the model, which is important in case of COVID-19. We found the stable equilibrium points of the mathematical model and compared the results of the model with those reported by the Chinese authorities and found a fit of approximately 96 percent. äTheta-SEIHRD mathematical model of Covid19-stability analysis using fa(epmc).pdf DeepDyve Pubget Overpricing