Fractals

In this paper, utilizing the theory of Watson transform and Watson convolution, we explore the Watson wavelet convolution product and its related properties. The relation between the Watson Wavelet convolution product and Watson convolution is also computed. Watson wavelet transform and its inversion formula are analyzed heuristically. Watson two-wavelet multipliers and its trace class are derived from Watson wavelet convolution product

The aim of this study is to design a novel stochastic solver through the Morlet wavelet neural networks (MWNNs) for solving the mathematical Layla and Majnun (LM) system. The numerical representations of the mathematical LM system have been presented by using the MWNNs along with the optimization is performed through the hybridization of the global and local search schemes. The local active-set (AS) and global genetic algorithm (GA) operators have been used to optimize an error-based merit function using the differential LM model and its initial conditions. The correctness of the MWNNs using the local and global operators is observed through the comparison of the obtained solutions and the Adams scheme, which is used as a reference solution. For the stability of the MWNNs using the global and local operators, the statistical performances with different operators have been provided using the multiple executions to solve the nonlinear LM system.

The main goal of this paper is to present a novel numerical scheme based on the Fibonacci wavelets for solving the brain tumor growth model governed by the Burgess equation. At the first instance, the Fibonacci-wavelet-based operational matrices of integration are obtained by following the well-known Chen–Hsiao technique. These matrices play a vital role in converting the said model into an algebraic system, which could be handled with any standard numerical method. To access the effect of medical treatment over the brain tumor growth, we have investigated both the linear and nonlinear cases of Burgess equation. The nonlinearity arising in the Burgess equation is handled by invoking the quasilinearization technique. In order to compare the efficiency of the Fibonacci-wavelet-based numerical technique, we formulated an analogous numerical scheme based on the Haar wavelets. Subsequently, both the methods are testified on several test problems and it is demonstrated that the Fibonacci wavelet method yields a much more stable solution and a better approximation than the Haar wavelet method.

In this paper, a hybrid approach is presented for the numerical solution of three-dimensional parabolic partial differential equations. This new approach is applicable to both linear and nonlinear parabolic problems including systems. This hybrid numerical technique is based on the Haar wavelet collocation technique and the finite difference method. In this technique, the space derivative is approximated by truncated Haar wavelet series whereas the time derivative is approximated by finite difference method. The aforementioned proposed algorithms are very simple and can easily be implemented in any computer-oriented language efficiently. In order to demonstrate the efficiency and better accuracy of the newly developed numerical technique it is applied to some well-known examples from previous literature that comprises linear and nonlinear three-dimensional parabolic equations including systems. The obtained results affirm better accuracy and widespread applicability of the newly proposed numerical technique for a range of benchmark problems.

In this paper, we consider a general system of fractal-fractional order derivative in Atangana–Baleanu–Caputo sense. On the application of fixed point approach, we establish sufficient conditions regarding existence and uniqueness of solution. The said requirements are obtained via using Krasnoselkii’s and Banach fixed results. Further via nonlinear analysis, some interesting results for Hyers–Ulam (HU)-type stability are also derived. To compute numerical solution for the proposed nonlinear system, fractal-fractional order Adams–Bashforth method is used. To support our findings, we give some test problems. Also by Matlab, we also present their graphical interpretation. The analysis of this paper is in generalized format which can be applied to any real problem. Each equation is investigated separately for the said characteristics.

The coupled fractional Fourier transform is a much recent ramification of the two-dimensional fractional Fourier transform, wherein the kernel is not a tensor product of one-dimensional copies, but relies on two angles that are coupled to yield a new pair of transform parameters. In this paper, we introduce a novel two-dimensional Wigner distribution, coined as coupled fractional Wigner distribution (CFrWD). The prime advantage of such a ramification of the Wigner distribution lies in the fact that the CFrWD can efficiently tackle the higher-order-phase and chirp signals, which constitute a wider class of signals arising in modern communication systems. To begin with, we study some fundamental properties of the proposed CFrWD, including marginal, shifting, conjugate-symmetry and anti-derivative properties. In addition, we also formulate the Moyal’s principle, inversion formula and the convolution and correlation theorems associated with CFrWD. Nevertheless, we demonstrate the efficacy of CFrWD for estimating and detecting both the one-component and multi-component linear-frequency-modulated signals.

In this paper, we deal with the numerical solution of the reaction–diffusion Ebola epidemic model. The diffusion which is an important phenomenon for the epidemic model is included in the model. This inclusion has made the model more comprehensive for studying the disease dynamics in the human population. The quantities linked with the model indicate the population sizes which are taken as absolute, therefore, the numerical schemes utilized to solve the underlying Ebola epidemic system should sustain the positivity. The numerical approaches used to solve the underlying epidemic models are explicit nonstandard finite difference operator splitting (ENSFD-OS) and implicit nonstandard finite difference operator splitting (INSFD-OS) techniques. These schemes preserve all the physical features of the state variables, i.e. projected schemes hold the positive solution acquired by the Ebola diffusive epidemic model. The underlying epidemic model illustrates two stable steady states, a virus-free state, and a virus existence state. The suggested approaches retain the stability of each of the steady states possessed by the assumed epidemic model. A numerical example and simulations for validation of all the characteristics of suggested techniques are also investigated.

A numerical method for the solution of nonlinear variable-order (VO) fractional differential equations (FDEs) is proposed in this paper. To determine the numerical solution of nonlinear VO FDEs, we used the Haar wavelet collocation method (HWCM) with a combination of Caputo fractional derivatives. For checking the efficiency of the HWCM, some examples are given. The maximum absolute error and mean square root errors of each test problem are computed for a different number of collocation points (CPs) to check the validity and applicability of the presented technique. The comparison of the exact and approximate solution is shown in figures for various numbers of CPs.

In this paper, we use Krasnoselskii’s fixed point theorem to find existence results for the solution of the following nonlinear fractional differential equations (FDEs) for a coupled system involving AB-Caputo fractional derivative

In this paper, the existence results for the solutions of the multi-term ABC-fractional differential boundary value problem (BVP)

This study shows the design of the Meyer wavelet neural networks (WNNs) to perform the numerical solutions of the spread of computer virus with kill signals, i.e. SEIR-KS system. The optimization of the SEIR-KS system is performed by the Meyer WNNs together with the optimization through the genetic algorithm (GA) and sequential quadratic (SQ) programming, i.e. Meyer WNNs-GASQ programming. A sigmoidal-based log-sigmoid function is implemented as an activation function, while 10 numbers of neurons work with 120 variables throughout this study. The correctness of the proposed Meyer WNNs-GASQP programming is observed through the comparison of the obtained and reference numerical solutions. For the consistency and reliability of the Meyer WNNs-GASQ programming, an analysis based on different statistical procedures is performed using 40 numbers of independent executions. Moreover, the use of different statistical operators like mean, median, minimum, standard deviation and semi-interquartile range further validates the correctness of the Meyer WNNs-GASQ programming for solving the SEIR-KS system.

Artificial Neural Network (ANN) is a supervised learning nonlinear complex model. This characteristic enables ANN to be used in nonlinear system modeling and classification applications. This research work proposed a technique called Wavelet Neural Network (WNN), and in the hidden layers of WNN, Morlet and Mexican are used as an activation function. During the processing, the WNN gets stuck in the local minimum causing slow convergence. For evaluating such kinds of problems, numerous algorithms have been tried and used. Consequently, this proposed research work used a novel meta-heuristic search technique called Accelerated Particle Swarm Optimization (APSO) algorithm combined with the WNN. Due to the effective convergence and fast searching toward an optimal solution, the APSO algorithm is used. In the proposed APSOWNN algorithm, APSO searches for the best sub-search solution. In conclusion, this model is assessed on the basis of total of three different datasets like the 4-bit OR, 7-bit Parity and IRIS benchmark classification problems, and its efficiency is equated with criterion methods such like Wavelet Back Propagation Neural Network (WBPNN), Artificial Bee Colony Wavelet Neural Network (ABCWNN) and WNN. Finally, from the results of simulation, it has been concluded that the proposed algorithm’s performance is much better, as compared to the state-of-the-art algorithms in terms of mean square error.(MSE) and accuracy.

There is considerable literature on solutions to the gas-dynamic equation (GDE) and Fokker–Planck equation (FPE), where the fractional derivative is expressed in terms of the Caputo fractional derivative. There is hardly any work on analytical and numerical GDE and FPE solutions involving conformable fractional derivative (CFD). For the reasons stated above, we are required to solve the GDE and FPE in the form of CFD. The main goal of this research is to offer a novel combined method by employing the conformable Shehu transform (CST) and the homotopy perturbation method (HPM) for extracting analytical and numerical solutions of the time-fractional conformable GDE and FPE. The proposed method is called the conformable Shehu homotopy perturbation method (CSHPM). To evaluate its efficiency and consistency, relative and absolute errors among the approximate and exact solutions to three nonlinear problems of GDE and FPE are considered numerically and graphically. Moreover, fifth-term approximate and exact solutions are also compared by 2D and 3D graphs. This method has the benefit of not requiring any minor or major physical parameter assumptions in the problem. As a result, it may be used to solve both weakly and strongly nonlinear problems, overcoming some of the inherent constraints of classic perturbation approaches. Second, while addressing nonlinear problems, the CSHPM does not require Adomian polynomials. Therefore, to solve nonlinear GDE and FPE, just a few computations are necessary. As a consequence, it outperforms homotopy analysis and Adomian decomposition approaches significantly. It does not require discretization or linearization, unlike traditional numerical methods. The convergence and error analysis of the series solutions are also presented.

This work aims at a new semi-analytical method called the variational iteration transform method for investigating fractional-order Emden–Fowler equations. The Shehu transformation and the iterative method are applied to achieve the solution of the given problems. The proposed method has the edge over other techniques as it does not required extra calculations. Some numerical problems are used to test the validity of the suggested method. The solution obtained has demonstrated that the proposed technique has a higher level of accuracy. The proposed method is capable of tackling various nonlinear fractional-order problems due to its simple implementation.

The inversion formula of the continuous Bessel wavelet transform of distributions is investigated by exploiting the theory of the Hankel transform. Some auxiliary results related to the inversion formula are also obtained in this paper. Using the theory of inversion formula of continuous Bessel wavelet transform of distributions, the Calderón reproducing formula is developed. The continuous Bessel wavelet transform of distributions through heat equation is discussed and its inversion formula is considered.

In this paper, Hermite wavelet method (HWM) is considered for numerical solution of 12- and 13-order boundary value problems (BVPs) of ordinary differential equations (ODEs). The proposed algorithm for HWM developed in Maple software converts the ODEs into an algebraic systems of equations. These algebraic equations are then solved by evaluating the unknown constants present in the system of equations and the approximate solution of the problem is obtained. Test problems are considered and their solutions are investigated using HWM-based algorithm. The obtained results from the test problems are compared with exact solution, and with other numerical methods solution in the existing literature. Results comparison are presented both graphically and in tabular form showing close agreement with exact solution, and greater accuracy than homotopy perturbation method (HPM) and differential transform method (DTM).

In this paper, the model for bovine babesiosis epidemic transmission is analyzed using a fractional operator with a Mittag-Leffler kernel. The existence and uniqueness of the solution of the considered model is studied using real analysis. The Hyers–Ulam (HU) stability is investigated with the help of nonlinear functional analysis. The numerical results of the proposed model are deduced through the Adams–Bashforth technique, which is based on the two-step Lagrangian interpolation method. All results are simulated for a few fractional orders to observe the dynamics of the proposed model.

In this paper, a new Meyer neuro-evolutionary computational algorithm is introduced for mathematical modeling of the epidemiological smoking model by employing hybrid heuristics of Meyer wavelet neural network with global optimized search efficiency of genetic algorithm and sequential quadratic programming. According to the World Health Organization, tobacco consumption kills 10% of all adults worldwide. The smoking epidemic is often regarded as the greatest health threat that humanity has ever confronted. So it’s an important issue to address by employing hybrid suggested techniques. The Meyer wavelet modeling approach is exploited to describe the system model epidemiological smoking in a mean squared error-based function, and the systems are optimized using the proposed approach’s combined optimizing capability. Root mean square error, Theil’s inequality factor, and mean absolute deviation-based measurements are used to better verify the effectiveness of the suggested methodology. The combined approach for smoking model is verified, validated, and perfected through comparison investigations of reference results on stability, precision, convergence, and reliability criteria, which shows the novelty of this study. Furthermore, the results of the quantitative study support the value of the suggested approach-based stochastic algorithm. The values of absolute error lie between $10^{-2}$ and $10^2$, $10^{-6}$ and $10^{-3}$, $10^{-6}$ and $10^{-4}$, $10^{-6}$ and $10^{-3}$, $10^{-5}$ and $10^{-4}$, and $10^{-6}$ and $10^{-5}$. The convergence measurement values for Theil’s inequality coefficient lie between $10^{-5}$ and $10^0$, $10^{-10}$ and $10^{-5}$, $10^{-10}$ and $10^{-5}$, $10^{-10}$ and $10^{-5}$, $10^{-10}$ and $10^{-5}$, and $10^{-10}$ and $10^{-5}$.

The human immunodeficiency virus (HIV) is a major global public health issue and causes millions of deaths around the globe. The most severe phase of HIV infection is known as AIDS. In recent years, a number of mathematical models based on classical integer-order derivative have been developed to analyze the insight dynamics of HIV/AIDS. This paper presents the transmission dynamics of HIV/AIDS using fractional order (FO) and a fractal-fractional order compartmental model with the power-law kernel. In the first phase, the proposed model is formulated using the Caputo-type fractional derivative. The basic properties such as the solution positivity and existence as well as uniqueness of the fractional model are presented. The equilibria and the basic reproductive number ${{ℛ}}_0$ are evaluated. Further, using fractional stability concepts the stability of the model (both local and global) around the equilibrium is presented in the disease-free case. In addition, the fractional model is solved numerically, and the graphical results with many values of $q_1$ are shown. In the second phase, the concept of a fractal-fractional (FF) operator is applied to obtain a more generalized model that addresses the dynamics of HIV/AIDS. The uniqueness and existence of the solutions of the FF-based model are shown via the Picard–Lindelof approach while the modified Adams–Bashforth method is utilized to present the numerical solution. Detailed numerical simulations are presented for various values fractional as well as the fractal orders, $q_1$ and $q_2,$ respectively. The graphical results reveal that the FF-based model provides biologically more feasible results than the models in fractional and classical integer-order cases.

In this research paper, we find the numerical solutions of fractional order scalers and coupled system of differential equations under initial conditions using shifted Legendre polynomials. By using the properties of shifted Legendre polynomials, we establish operational matrices of integration and differentiation in order to simplify our considered problems under initial conditions. In order to check the accuracy of the proposed model, some test problems are solved along with the graphical representations. For coupled system, we applied the algorithm to the Pharmacokinetic two-compartment model. As the proposed method is computer-oriented, we use therefore the MATLAB for required calculations. Numerical results are shown graphically.

This paper is related to some qualitative results about the existence and uniqueness of a solution to a third-order problem by using a fixed point approach. Haar technique is applied for numerical solution of a third-order linear integro-differential equation (IDE) with initial conditions. In IDE, the third-order derivative is computed by Haar functions, and the integration is used to get the expression of second- and first-order derivatives, as well as an approximate solution. Some examples from the literature are used to verify the validity of the proposed method. Error analysis is performed. Also, comparison between the exact and numerical solutions at different collocation points (CPs) is derived. The convergence rate is recorded taking different numbers of CPs, which is approximately equal to 2.

Fractional order integro-differential equation (FOIDE) of Fredholm type is considered in this paper. The mentioned equations have many applications in mathematical modeling of real world phenomenon like image and signal processing. Keeping the aforementioned importance, we study the considered problem from two different aspects which include the existence theory and computation of numerical approximate solution. FOIDEs have been investigated very well by using Caputo-type derivative for the existence theory and numerical solutions. But the mentioned problems have very rarely considered under the Mittage-Leffler-type derivative. Also, for FOIDE of Fredholm type under Mittage-Leffler-type derivative has not yet treated by using Haar wavelet (HW) method. The aforementioned derivative is non-singular and nonlocal in nature as compared to classical Caputo derivative of fractional order. In many cases, the nonsingular nature is helpful in numerical computation. Therefore, we develop the existence theory for the considered problem by using fixed point theory. Sufficient conditions are established which demonstrate the existence and uniqueness of solution to the proposed problem. Further on utilizing HW method, a numerical scheme is developed to compute the approximate solution. Various numerical examples are given to demonstrate the applicability of our results. Also, comparison between exact and numerical solution for various fractional orders in the considered examples is given. Numerical results are displayed graphically.

In this paper, Haar wavelet collocation method (HWCM) for nonlinear delay Volterra, delay Fredholm and delay Volterra–Fredholm Integro-Differential Equations (IDEs) are studied numerically using HWCM. This method is very useful for solving nonlinear IDEs. The technique (HWCM) reduced the given equations into a system of nonlinear algebraic equations. The nonlinear system is then solved by Broydens technique. Some numerical examples are taken from literature for the validation purpose, computational efficiency and convergence of the proposed method. The approximate solution is compared with the exact solution and the maximum absolute and mean square root errors are presented for each example in tables. The comparison between exact and approximate solution is shown in figures for each example. The results are compared with existing methods from the literature. The results exhibit that the HWCM is simple, precise and efficient.

In this paper, we introduce a new method to create a series solution to the time-fractional Navier–Stokes equations using a combination of the Laplace transform with the optimal homotopy asymptotic method. Caputo’s derivative was applied in the present technique. Three test problems are carried out to validate and demonstrate the method’s efficacy. The system has been found to be a very reliable, effective and powerful technique for solving the proposed model as well as a variety of engineering and science problems.