Showing papers in "Journal of Computational and Applied Mathematics in 2020"

TL;DR: This investigation of Bitcoin price prediction can be considered a pilot study of the importance of the sample dimension in machine learning techniques, with accuracy reaching 67.2%.

TL;DR: A stochastic gradient algorithm and a gradient-based iterative algorithm for estimating the parameters of the systems in the case of the known input–output data by means of the auxiliary model are presented.

TL;DR: Fractional discrete-time recurrent neural network is proposed on an isolated time scale and short memory and variable-order fractional neural networks are given according to the stability conditions.

TL;DR: The research shows that in each cluster area, the factors that significantly affect the green innovation efficiency of high-tech industry are different, and the degree of influence of each factor on the innovation efficiency at different quantile is also different.

TL;DR: A novel model for remote sensing images destriping is proposed, which includes the Schatten 1 ∕ 2 -norm and the unidirectional first-order and high-order total variation regularization and the alternating direction method of multipliers algorithm to solve the proposed model.

TL;DR: This paper proposes the partial sum of the tubal nuclear norm (PSTNN) of a tensor, a surrogate of the tensor tubal multi-rank, and builds two PSTNN-based minimization models for two typical tensor recovery problems, i.e., the Tensor completion and the tensar principal component analysis.

TL;DR: New integral inequalities of midpoint and trapezoid type for twice differentiable convex functions in a form classical integral and Riemann–Liouville fractional integrals are obtained and applied to construct inequalities involving moments of a continuous random variable.

TL;DR: A new numerical scheme based on two steps Newton polynomial is introduced for both ordinary differential equations with classical and fractional derivative and some applications and illustrative examples are presented.

TL;DR: A novel numerical technique for fractal–fractional model with many graphical results for data fitting with the suggested operators and shows that these two operators give the same results for the data fitting but varying both the values of the fractal and fractional order the authors have reasonable results.

TL;DR: A projection method combined with Fast Fourier Transform (FFT) is applied to value equity-linked death benefit products and various numerical valuation results computed by B-spline functions are presented to demonstrate the method’s efficiency and accuracy.

TL;DR: A sixth-kind Chebyshev collocation method will be considered for solving a class of variable order fractional nonlinear quadratic integro-differential equations (V-OFNQIDEs) to validate the accuracy and robustness of the proposed approach.

TL;DR: The authors prove that the function x is strictly increasing on 1, ∞ for fixed p ≥ 1, which not only yields sharp lower and upper bounds of the ratio ζ x + p ∕ζ x for x ∈ a, b ( b > a ≥ 1 ), but also leads to the best lower andupper bounds for the ratio of any two Bernoulli numbers.

TL;DR: The outcomes show that the surface stresses have a significant effect on the increases of the frequency and buckling load and decrease of the deflection.

TL;DR: The results support the government in Japan and India to keep its steps to regard financial development as an instrument to foster economic growth, and economic growth is considered as an engine to promote financial development for sustainability.

TL;DR: An analogue of Taylor’s theorem and some integral inequalities are proved to enrich the mathematical theory of tempered fractional calculus.

TL;DR: In this article, the authors considered a class of nonlinear integro-differential equations of variable-order, and they used operational matrices based on the shifted Legendre polynomials to approximate the unknown function and its derivatives.

TL;DR: Using the RF algorithm and BP neural network method in machine learning to explore the problems of Internet finance is of great significance for risk prediction for other financial institutions.

TL;DR: It is shown that stochastic integro-differential equation of fractional order is equivalent to a modified stochastically integral equation, and the proposed method is applied to obtain a numerical scheme of the modified Stochastic integral equation.

TL;DR: The panel data model and the spatial econometric methods are used to explore the relationship between innovative human capital and provincial economies (regional economies with varying degrees of openness) and it is hoped this paper can provide guide for the Chinese overall region coordinated development and the provinces with low innovativeHuman capital, which is caused by the low degree of openness.

TL;DR: It is proved that the present problem is not well-posed and regularized problems are constructed using the truncated expansion method and the quasi-boundary value method in the case of two-dimensional and multi-dimensional time fractional reaction–diffusion equation.

TL;DR: A new weak Galerkin (WG) finite element method for second order elliptic equations on polytopal meshes designed by using a discrete weak gradient operator applied to discontinuous piecewise polynomials on finite element partitions of arbitrary polytopes with certain shape regularity is introduced.

TL;DR: The maximum likelihood estimators (MLEs) are developed for estimating the unknown parameters and the Bayesian estimates are evaluated by using the Lindley's approximation as well as the Monte Carlo Markov chain technique together with Metropolis–Hastings algorithm.

TL;DR: In this article, an optimal order uniformly accurate boundary layer adaptive method moving mesh method is proposed, which is able to capture the layer phenomena without using a priori information of the solution.

TL;DR: This work considers a class of fractional order Volterra integro-differential equations of first kind where the fractional derivative is considered in the Caputo sense and obtains sufficient conditions for the existence and uniqueness of the solutions of initial and the boundary value problems.

TL;DR: Deep learning neural network model can be applied to block chain financial transactions as a reference for financial transactions, which has a good practical significance for the development of this field.

TL;DR: The results show that BPNN has unique advantages in solving such highly non-linear problems as evaluation of risks of the supply chain, and will provide a good reference for enterprises and other financial institutions to expand the financing business of supply chain and facilitate the evaluation of enterprise credit risk.

TL;DR: This paper proposes more favored novel non-local fractional integral and derivative operators with three parameters by using the iteration manner on truncated M -derivative involving truncated Mittag-Leffler function to solve Sturm–Liouville problem subjected to the initial conditions.

TL;DR: The slip flow of an unsteady incompressible Oldroyd-B fluid model is investigated and numerical Stehfest algorithm is used in place of promoting an analytical expression for inverse Laplace transform to have the validity of results.

TL;DR: Numerical evidence confirms that such scheme can be applied to mitigate Runge and Gibbs phenomena and is referred to as a new method for univariate polynomial interpolation based on what is called mapped bases.

TL;DR: Two new algorithms are proposed for solving an equilibrium problem whose associated bifunction is monotone and satisfies a Lipschitz-type condition in a Hilbert space and are constructed around the proximal-like mapping and the regularized method.