The fuzzy fractional SIQR model of computer virus propagation in wireless sensor network using Caputo Atangana–Baleanu derivatives

Dong, Nguyen Phuong; Long, Hoàng Việt; Giang, Nguyễn Long

doi:10.1016/j.fss.2021.04.012

Cited by 19 publications

(2 citation statements)

References 45 publications

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“…This new ABC derivative has a great memory due to the existence of Mittag–Leffler function as its nonlocal kernel; eventually, it results in a better comparative performance as compared to other existing fractional derivative operators. Validation of the above claim is justified by applying ABC operator, instead of other operators, and solving various scientific models, namely, the general sequential hybrid class of FDEs [15, 16], controllability of neutral impulsive [17], Covid‐19 mathematical model [18, 19], fractional typhoid model [20], wireless sensor network as an application of the fuzzy fractional SIQR model [21], plasma particle model with circular LASER light polarization [22], Hepatitis B model [23], SEIR and blood coagulation technologies [24], a fractal‐fractional tuberculosis [25] and tobacco [26] mathematical model, a class of population growth model [27], and the fractional nonlinear logistic system [27].…”

Section: Introductionmentioning

confidence: 99%

Solution of fractional Sawada–Kotera–Ito equation using Caputo and Atangana–Baleanu derivatives

Khirsariya

Rao

2023

Math Methods in App Sciences

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In the present work, the fractional‐order Sawada–Kotera–Ito problem is solved by considering nonlocal Caputo and nonsingular Atangana–Baleanu (ABC) derivatives. The methodology used is an application of the Shehu transform and the Adomian decomposition method. The obtained solution is more accurate when using the ABC type derivative as compared to the Caputo sense, when using the proposed ADShTM method (Adomian decomposition Shehu transform method). The results so obtained by the ADShTM using Caputo and ABC operators are compared, establishing the superiority of the proposed method. The numerical results demonstrate that the application of the ABC derivative is not only relatively more effective and reliable but also straightforward to achieve high precision solution.

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Section: Introductionmentioning

confidence: 99%

Solution of fractional Sawada–Kotera–Ito equation using Caputo and Atangana–Baleanu derivatives

Khirsariya

Rao

2023

Math Methods in App Sciences

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“…Fractional calculus is widely used in various fields of science and technology, e.g., in the design of sensors, in signal processing, and network sensors [1][2][3][4][5]. In the paper [2], authors describe the use of fractional calculus for artificial neural networks.…”

Section: Introductionmentioning

confidence: 99%

Computational Methods for Parameter Identification in 2D Fractional System with Riemann–Liouville Derivative

Brociek

Wajda

Sciuto

et al. 2022

Sensors

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In recent times, many different types of systems have been based on fractional derivatives. Thanks to this type of derivatives, it is possible to model certain phenomena in a more precise and desirable way. This article presents a system consisting of a two-dimensional fractional differential equation with the Riemann–Liouville derivative with a numerical algorithm for its solution. The presented algorithm uses the alternating direction implicit method (ADIM). Further, the algorithm for solving the inverse problem consisting of the determination of unknown parameters of the model is also described. For this purpose, the objective function was minimized using the ant algorithm and the Hooke–Jeeves method. Inverse problems with fractional derivatives are important in many engineering applications, such as modeling the phenomenon of anomalous diffusion, designing electrical circuits with a supercapacitor, and application of fractional-order control theory. This paper presents a numerical example illustrating the effectiveness and accuracy of the described methods. The introduction of the example made possible a comparison of the methods of searching for the minimum of the objective function. The presented algorithms can be used as a tool for parameter training in artificial neural networks.

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A creep constitutive model based on Atangana–Baleanu fractional derivative

Deng

Zhou

Wei

et al. 2022

Mech Time-Depend Mater

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The fuzzy fractional SIQR model of computer virus propagation in wireless sensor network using Caputo Atangana–Baleanu derivatives

Cited by 19 publications

References 45 publications

Solution of fractional Sawada–Kotera–Ito equation using Caputo and Atangana–Baleanu derivatives

Solution of fractional Sawada–Kotera–Ito equation using Caputo and Atangana–Baleanu derivatives

Computational Methods for Parameter Identification in 2D Fractional System with Riemann–Liouville Derivative

A creep constitutive model based on Atangana–Baleanu fractional derivative

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