In this study, the Laplace Adomian decomposition technique (LADT) is employed to analyse a numerical study with the SDIQR mathematical model of COVID-19 for infected migrants in Odisha. The analytical power series and LADT are applied to the Covid-19 model to estimate the solution profiles of the dynamical variables. We proposed a mathematical model that incorporates both the resistive class and the quarantine class of COVID-19. We also introduce a procedure to evaluate and control the infectious disease of COVID-19 through the SDIQR pandemic model. Five compartments like susceptible ( S ), diagnosed ( D ), infected ( I ), quarantined ( Q ) and recovered ( R ) population are found in our model. The model can only be solved approximately rather than analytically as it contains a system of nonlinear differential equations with reaction rates. To demonstrate and validate our model, the numerical simulations for infected migrants are plotted with suitable parameters.
In this paper, we develop and employ an efficient numerical technique for traveling wave solution of the Time Fractional Zakharov-Kuznetsov (TFZK) equation, also known as the nonlinear evolution equation, using the Modified Adomian Decomposition Approach (MADA) in collaboration with the cubic order convergence of the Newton-Raphson method (also known as the improvised Newton-Raphson method) on the Shehu Transform environment (STE). In the current study, the time fractional Caputo-Fabrizio Derivative (CFD) is used in singular and non-singular kernel derivatives to address the influence of fractional parameters. Some of the current numerical and analytical results are displayed utilizing 3D plots, while others are depicted in the form of a legend 2D plots for comparison. To validate the robustness of the current approach, the uniqueness, stability, and convergence analyses are described. The current result is compared to the analytical solution as well as previous solutions in order to demonstrate the efficiency of our suggested technique.
<p>The maximum power point tracking (MPPT) has been a popular terminology among those researchers who deal with one of the most available renewable energy resources called solar power. Many researchers have evolved and proposed a lot of techniques for tracking maximum power. But each technique has its pros and cons. Some techniques suffer from complexity as far as implementation is concerned, whereas other techniques lack accuracy. In current research work, it has been investigated the MPPT using Newton Raphson (NR) method, which has not yet received a good attention by researchers. After observing its limitation, this method is modified (i.e., abbreviated as modified Newton Raphson method (MNRM)) to make it suitable for extracting the maximum power from PV module. The feasibility and precision of this method depends upon accurate measurement of temperature and irradiation. By using MNRM, the presumption of initial value is close to the voltage corresponding to maximum power, so it leads faster converging to solution through a few rounds of iterations. In order to validate it, a MATLAB/Simulink model is developed and simulated. The proposed method is incorporated in PV module-fed buck converter so as to explore superior performance.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.