scholarly journals Fractional order COVID 19 pandemic model in Morocco: Dynamical analysis and Numerical simulation

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
mohammed gouda ◽  
ahmed elsayed ◽  
Ibrahim Hanafy ◽  
anas arafa
Keyword(s):  
Numerical Simulation ◽  
Fractional Order ◽  
Dynamical Analysis

DYNAMICAL ANALYSIS OF FRACTIONAL ORDER ZIKV MODEL

2021 ◽  
Vol 10 (5) ◽  
pp. 2469-2481
Author(s):  
N.A. Hidayati ◽  
A. Suryanto ◽  
W.M. Kusumawinahyu
Keyword(s):  
Numerical Simulation ◽  
Equilibrium Point ◽  
Fractional Order ◽  
Equilibrium Points ◽  
Dynamical Analysis ◽  
Stability Conditions ◽  
Order Model ◽  
Fractional Order Model ◽  
The Stability ◽  
S Model

The ZIKV model presented in this article is developed by modifying \cite{Bonyah2016}’s model. The classical order is changed into fractional order model. The equilibrium points of the model are determined and the stability conditions of each equilibrium point have been done using Routh-Hurwitz conditions. Numerical simulation is presented to verify the result of stability analysis result. Numerical simulation is also used to shows the effect of the order $\alpha$ to the stability of the model’s equilibrium point.

scholarly journals Dynamical analysis and adaptive fuzzy control for the fractional-order financial risk chaotic system

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Sukono ◽  
Aceng Sambas ◽  
Shaobo He ◽  
Heng Liu ◽  
Sundarapandian Vaidyanathan ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Fuzzy Control ◽  
Fractional Order ◽  
Chaotic System ◽  
Financial Risk ◽  
Chaotic Behavior ◽  
Dynamical Behavior ◽  
Adaptive Fuzzy Control ◽  
Dynamical Analysis ◽  
Adaptive Fuzzy

AbstractIn this paper, a fractional-order model of a financial risk dynamical system is proposed and the complex behavior of such a system is presented. The basic dynamical behavior of this financial risk dynamic system, such as chaotic attractor, Lyapunov exponents, and bifurcation analysis, is investigated. We find that numerical results display periodic behavior and chaotic behavior of the system. The results of theoretical models and numerical simulation are helpful for better understanding of other similar nonlinear financial risk dynamic systems. Furthermore, the adaptive fuzzy control for the fractional-order financial risk chaotic system is investigated on the fractional Lyapunov stability criterion. Finally, numerical simulation is given to confirm the effectiveness of the proposed method.

scholarly journals Complexity and Chimera States in a Network of Fractional-Order Laser Systems

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 341
Author(s):  
Shaobo He ◽  
Hayder Natiq ◽  
Santo Banerjee ◽  
Kehui Sun
Keyword(s):  
Numerical Simulation ◽  
Numerical Solution ◽  
Bifurcation Diagram ◽  
Fractional Order ◽  
Dynamical Model ◽  
Chimera States ◽  
Laser Systems ◽  
Complexity Algorithm ◽  
Derivative Order

By applying the Adams-Bashforth-Moulton method (ABM), this paper explores the complexity and synchronization of a fractional-order laser dynamical model. The dynamics under the variance of derivative order q and parameters of the system have examined using the multiscale complexity algorithm and the bifurcation diagram. Numerical simulation outcomes demonstrate that the system generates chaos with the decreasing of q. Moreover, this paper designs the coupled fractional-order network of laser systems and subsequently obtains its numerical solution using ABM. These solutions have demonstrated chimera states of the proposed fractional-order laser network.

Dynamical analysis of a fractional-order foot-and-mouth disease model

2021 ◽  
Vol 15 (1) ◽  
pp. 65-82
Author(s):  
Tinashe B. Gashirai ◽  
Senelani D. Hove-Musekwa ◽  
Steady Mushayabasa
Keyword(s):  
Fractional Order ◽  
Disease Model ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Dynamical Analysis ◽  
Foot And Mouth

Dynamical analysis of the improper fractional-order 2D-SCLMM and its DSP implementation

2021 ◽  
Vol 136 (5) ◽  
Author(s):  
Tianming Liu ◽  
Santo Banerjee ◽  
Huizhen Yan ◽  
Jun Mou
Keyword(s):  
Fractional Order ◽  
Dynamical Analysis ◽  
Dsp Implementation

Numerical simulation and dynamical analysis for low salinity water lens in the expansion area of the Changjiang diluted water

2014 ◽  
Vol 28 (6) ◽  
pp. 777-790 ◽  
Author(s):  
Wen-jing Zhang ◽  
Shou-xian Zhu ◽  
Xun-qiang Li ◽  
Kun Ruan ◽  
Wei-bing Guan ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Dynamical Analysis ◽  
Changjiang Diluted Water ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water

scholarly journals Dynamical analysis of fractional-order of IVGTT glucose-insulin interaction

2020 ◽  
Author(s):  
Sayed Saber ◽  
Mansoor Alshehri ◽  
Faisal Duraihem ◽  
Mohamed Abdelkawy
Keyword(s):  
Fractional Order ◽  
Dynamical Analysis

scholarly journals Analysis of Atangana–Baleanu fractional-order SEAIR epidemic model with optimal control

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chernet Tuge Deressa ◽  
Gemechis File Duressa
Keyword(s):  
Numerical Simulation ◽  
Optimal Control ◽  
Fractional Order ◽  
Control Strategy ◽  
Epidemic Model ◽  
Numerical Scheme ◽  
Order Derivative ◽  
Control Analysis ◽  
Fractional Order Derivative ◽  
Fractional Orders

AbstractWe consider a SEAIR epidemic model with Atangana–Baleanu fractional-order derivative. We approximate the solution of the model using the numerical scheme developed by Toufic and Atangana. The numerical simulation corresponding to several fractional orders shows that, as the fractional order reduces from 1, the spread of the endemic grows slower. Optimal control analysis and simulation show that the control strategy designed is operative in reducing the number of cases in different compartments. Moreover, simulating the optimal profile revealed that reducing the fractional-order from 1 leads to the need for quick starting of the application of the designed control strategy at the maximum possible level and maintaining it for the majority of the period of the pandemic.

Initialization of Identification of Fractional Model by Output-Error Technique

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
Abir Khadhraoui ◽  
Khaled Jelassi ◽  
Jean-Claude Trigeassou ◽  
Pierre Melchior
Keyword(s):  
Numerical Simulation ◽  
Least Squares ◽  
Fractional Order ◽  
Fractional Integration ◽  
New Approach ◽  
Fractional Model ◽  
Output Error

A bad initialization of output-error (OE) technique can lead to an inappropriate identification results. In this paper, we introduce a solution to this problem; the basic idea is to estimate the parameters and the fractional order of the noninteger system by a new approach of least-squares (LS) method based on repeated fractional integration to initialize OE technique. It will be shown that LS method offers a good initialization to OE algorithm and leads to acceptable identification results. The performance of the proposed method is shown through numerical simulation examples.

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