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An efficient inertial subspace minimization CG algorithm with convergence rate analysis for constrained nonlinear monotone equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-11 Taiyong Song, Zexian Liu
Conjugate gradient (CG) methods are efficient algorithms for unconstrained optimization. An inertial step strategy is usually used to accelerate iterative methods. In 1995, Yuan and Stoer (1995) introduced a subspace study on CG algorithms and presented some subspace minimization CG (SMCG) methods. Motivated by these approaches, we incorporate a new inertial step strategy in SMCG methods and present
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Lattice factorization based causal symmetric paraunitary matrix extension and construction of symmetric orthogonal multiwavelets J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-11 ChiWon Ri
In this paper, we propose a lattice factorization based symmetric paraunitary matrix extension method to design a causal symmetric paraunitary multifilter banks(PUMFBs) and construct compactly supported symmetric orthogonal multiwavelets by using the method.
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Small area estimation with partially linear mixed-t model with measurement error J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-11 Seyede Elahe Hosseini, Davood Shahsavani, Mohammad Reza Rabiei, Mohammad Arashi
In small area estimation (SAE), using direct conventional methods will not lead to reliable estimates because the sample size is small compared to the population. Small Area Estimation under Fay Herriot Model is used to borrow strength from auxiliary variables to improve the effectiveness of a sample size. However, the normality assumption is a limiting assumption for heavy-tailed data and outlying
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Numerical analysis of light-controlled drug delivery systems J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-07 J.A. Ferreira, H.P. Gómez, L. Pinto
In this paper, we solve a non-linear reaction–diffusion system with Dirichlet–Neumann mixed boundary conditions using a finite difference method (FDM) in space and the implicit midpoint method in time. This type of system appears, e.g., in the mathematical modeling of light-controlled drug delivery. One of the key results of this paper is the proof that the method has superconvergence second-order
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A family of two-step second order Runge–Kutta–Chebyshev methods J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-07 Andrew Moisa
In this paper, a new family of second order two-step Runge–Kutta–Chebyshev methods is presented. These methods are a generalization of the one-step stabilized methods and have better computational properties compared to them. A new code TSRKC2 is developed and compared to existing solvers at sufficiently large set of examples.
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An efficient numerical scheme to solve generalized Abel’s integral equations with delay arguments utilizing locally supported RBFs J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-06 Alireza Hosseinian, Pouria Assari, Mehdi Dehghan
Hereditary effects are commonly observed in diverse scientific domains such as engineering, economics, biology, mathematics, and physics. In the model of atomic irradiation of solids with unbounded cross-sectional areas, determining the average number of atoms displaced has been achieved through delay systems that incorporate the consideration of past states. In this study, we employ the discrete collocation
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On approximation for time-fractional stochastic diffusion equations on the unit sphere J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-06 Tareq Alodat, Quoc T. Le Gia, Ian H. Sloan
This paper develops a two-stage stochastic model to investigate the evolution of random fields on the unit sphere in . The model is defined by a time-fractional stochastic diffusion equation on governed by a diffusion operator with a time-fractional derivative defined in the Riemann–Liouville sense. In the first stage, the model is characterized by a homogeneous problem with an isotropic Gaussian random
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Midpoint splitting methods for nonlinear space fractional diffusion equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-06 Hongliang Liu, Tan Tan
We propose a midpoint splitting method to solve nonlinear space fractional diffusion equations. We first discretize the equation in space using the weighted and shifted Grünwald difference (WSGD) operators. Then, we obtain the fully discrete scheme of the equation using the midpoint splitting method, which can alleviate computational costs and mitigate instability issues that may arise. We establish
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Pricing longevity bond with affine-jump-diffusion multi-cohort mortality model J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-06 Jingtong Xu, Xu Chen, Yuying Yang
Facing increasingly severe longevity problems, traditional longevity risk management methods are no longer the final answer. Longevity risk securitization provides a good hedging method, which transfers the longevity risks to a wider capital market and realizes the cross-market transfer of risks. The pricing process of longevity derivatives depends on the underlying risk factors (stochastic processes
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FDM/FEM for nonlinear convection–diffusion–reaction equations with Neumann boundary conditions—Convergence analysis for smooth and nonsmooth solutions J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-05 J.A. Ferreira, G. Pena
This paper aims to present in a systematic form the stability and convergence analysis of a numerical method defined in nonuniform grids for nonlinear elliptic and parabolic convection–diffusion–reaction equations with Neumann boundary conditions. The method proposed can be seen simultaneously as a finite difference scheme and as a fully discrete piecewise linear finite element method. We establish
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An uncertainty theory based tri-objective behavioral portfolio selection model with loss aversion and reference level using a modified evolutionary root system growth algorithm J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-05 Yuefen Chen, Bo Li
The outbreak of uncertain events, e.g., financial crisis, regional conflict and abrupt contagion, has a significant impact on residents’ income. Hence, the wealth management and portfolio selection become more and more important. In addition, the behavioral finance believes that decision-making process of the investors not only depend on utility maximization, but also on who to compare with. It differs
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Some stabilities of stochastic differential equations with delay in the G-framework and Euler–Maruyama method J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-05 Haiyan Yuan, Quanxin Zhu
This paper discusses some stabilities of stochastic differential equations with delay in the G-framework (G-SDDEs, in short) and Euler-Maruyama method. We construct a weaker condition instead of using the Lyapunov functional method to obtain the -th moment exponential stability of the G-SDDE. We prove that the Euler-Maruyama method can reproduce the -th moment exponential stability of the G-SDDE under
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A sublinear functional based approximated equivalence to optimality and duality for multiobjective programming in complex spaces J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-04 Nisha Pokharna, Indira P. Tripathi
In this paper, we introduce a new approximation approach for a class of multiobjective programming problems in complex spaces and their duals. Using a sublinear functional, an approximated problem is constructed at a given feasible solution of the original problem. The equivalence between the solution of the considered multiobjective complex programming problem and its approximated problem is established
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A two-level finite element method with grad-div stabilizations for the incompressible Navier–Stokes equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-04 Yueqiang Shang
This article presents and studies a two-level grad-div stabilized finite element discretization method for solving numerically the steady incompressible Navier–Stokes equations. The method consists of two steps. In the first step, we compute a rough solution by solving a nonlinear Navier–Stokes system on a coarse grid. And then, in the second step, we pass the coarse grid solution to a fine grid to
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Unconditional error analysis of linearized BDF2 mixed virtual element method for semilinear parabolic problems on polygonal meshes J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-04 Wanxiang Liu, Yanping Chen, Jianwei Zhou, Qin Liang
In this paper, we construct, analyze, and numerically validate a class of -mixed virtual element method for the semilinear parabolic problem in mixed form, in which the parabolic problem is reformulated in terms of the velocity and the pressure of the time-dependent Darcy flow. The Newton linearized method for the nonlinear term is designed to cooperate with the second-order backward differentiation
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A numerical solution of singularly perturbed Fredholm integro-differential equation with discontinuous source term J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-03-01 Ajay Singh Rathore, Vembu Shanthi
In this paper, we investigate a singularly perturbed Fredholm integro-differential problem with a discontinuous source term, leading to the formation of interior layers in the solution at the point of discontinuity. We apply the exponentially fitted mesh method to solve the problem. Our analysis demonstrates that the method exhibits almost first-order convergence in the maximum norm, independent of
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Performance enhancement through portfolio optimization of delayed insider information: An analysis and implementation study J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-28 Sandra Ranilla-Cortina, Jesús Vigo-Aguiar
This paper addresses the classical problem of in a financial market where an with privileged information exists, along with a in the information flow. The paper calculates the wealth evolution process and determines the optimal portfolio that maximizes the expected final wealth for various well-known financial models, including Black–Scholes-Merton, Heston, Vasicek, Hull–White, and Cox-Ingersoll-Ross
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A monolithic space–time temporal multirate finite element framework for interface and volume coupled problems J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-28 Julian Roth, Martyna Soszyńska, Thomas Richter, Thomas Wick
In this work, we propose and computationally investigate a monolithic space–time multirate scheme for coupled problems. The novelty lies in the monolithic formulation of the multirate approach as this requires a careful design of the functional framework, corresponding discretization, and implementation. Our method of choice is a tensor-product Galerkin space–time discretization. The developments are
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On the compound Poisson phase-type process and its application in shock models J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-28 Dheeraj Goyal, Min Xie
In this paper, the compound Poisson phase-type process is defined and analyzed. This paper proves that for a non-negative compound Poisson phase-type process, the compound value for all the arrivals by a given time can be approximated by a phase-type distribution. As an application of this process, three different shock models are studied: the cumulative shock model, a degradation-threshold-shock model
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Construction of Bézier surfaces with minimal quadratic energy for given diagonal curves J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-27 Yong-Xia Hao, Wen-Qing Fei
Diagonal curve is one of the most important shape measurements of tensor-product Bézier surfaces. An approach to construct Bézier surfaces with energy-minimizing from two prescribed diagonal curves is presented in this paper. Firstly, a general second order functional energy is formulated with several parameters. This functional includes many common functionals as special cases, such as the Dirichlet
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A color image fusion model by saturation-value total variation J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-27 Wei Wang, Yuming Yang
In this paper, we propose and develop a novel color image fusion model by using saturation-value total variation. In the proposed model, we develop a variational approach containing an energy functional to determine the weighting mask functions and the fused image together. The objective fused image is modeled by using the saturation-value total variation regularization. The data-fitting term is formulated
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Dynamical analysis and explicit traveling wave solutions to the higher-dimensional generalized nonlinear wave system J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-24 Hanze Liu, Adilai Yusupu
For dealing with exact solutions and properties of PDEs, the higher-dimensional equations are far more complicated than the lower dimensional ones. In the current paper, by using the dynamical system method, we study the -dimensional generalized nonlinear coupled KdV (c-KdV) system, which includes a lot of important c-KdV types of systems as its special case. The bifurcations and phase portraits of
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A family of [formula omitted] four-point stationary subdivision schemes with fourth-order accuracy and shape-preserving properties J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-23 Hyoseon Yang, Kyungmi Kim, Jungho Yoon
The four-point interpolatory scheme and the cubic B-spline are examples of the most well-known stationary subdivision procedures. They are based on the space of cubic polynomials and have their respective strengths and weaknesses. In this regard, the purpose of this study is to introduce a new type of subdivision scheme that integrates the advantages of both the four-point and the cubic B-spline schemes
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Automated importance sampling via optimal control for stochastic reaction networks: A Markovian projection–based approach J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-23 Chiheb Ben Hammouda, Nadhir Ben Rached, Raúl Tempone, Sophia Wiechert
We propose a novel alternative approach to our previous work (Ben Hammouda et al., 2023) to improve the efficiency of Monte Carlo (MC) estimators for rare event probabilities for stochastic reaction networks (SRNs). In the same spirit of Ben Hammouda et al. (2023), an efficient path-dependent measure change is derived based on a connection between determining optimal importance sampling (IS) parameters
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Quantile Hedging in the complete financial market under the mixed fractional Brownian motion model and the liquidity constraint J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-22 Bing Cui, Alireza Najafi
This article proposes a pricing framework for European option that utilizes a Quantile hedging strategy in a complete financial market. The methodology involves applying the long memory Geometric Brownian motion model, utilizing the generalized mixed fractional Girsanov theorem, and incorporating relevant findings related to quasi-conditional expectation. The first step in this framework is to derive
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Nonparametric modal regression with mixed variables and application to analyze the GDP data J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-22 Zhong-Cheng Han, Yan-Yong Zhao
Modal regression is as efficient as mean regression when the random error follows normal distribution, and is robust to the presence of outliers or skewed distributions. Due to such advantages as efficiency and robustness, it has been widely applied in different fields, such as medicine, economics, environment and so on. However, most existing literature based on modal regression are assumed that the
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Improved model reduction with basis enrichment for dynamic analysis of nearly periodic structures including substructures with geometric changes J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-22 Jean-Mathieu Mencik
Model reduction based on matrix interpolation provides an efficient way to compute the dynamic response of nearly periodic structures composed of substructures (cells) with varying properties. This may concern 2D or 3D substructures subjected to geometric modifications (mesh variations) or more classic dimension changes. An efficient interpolation strategy for a nearly periodic structure can be obtained
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An upwind-mixed volume element method on changing meshes for compressible miscible displacement problem J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-21 Yuan Yirang, Li Changfeng, Song Huailing
Numerical simulation of oil-water miscible displacement is discussed in this paper, and a compressible problem of energy mathematics is solved potentially. The mathematical model defined by a nonlinear system includes mainly two partial differential equations (PDEs): a parabolic equation for the pressure and a convection-diffusion equation for the saturation. The pressure is obtained by a conservative
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Portfolio-consumption choice problem with voluntary retirement and consumption constraints J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-21 Ruifeng Mai, Zhou Yang, Yingyi Lai, Jianwei Lin
We study the investment–consumption choice problem with voluntary retirement and upside/downside consumption constraints in infinite horizon, which can be formulated as a two-phase mixed stochastic control problem including stopping time coupled with controls. By verification theorem, we show the strong solution of a fully nonlinear differential variational inequality, satisfying some special properties
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Mapped Gegenbauer functions for solving Hammerstein generalized integral equations with Green’s kernels on the whole line J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-21 Walid Remili, Azedine Rahmoune, Abdselam Silem
This paper introduces a collocation method for numerically solving Hammerstein generalized integral equations on the whole line. The approach utilizes mapped Gegenbauer functions to transform the Hammerstein integral equation into a system of nonlinear algebraic equations. Additionally, convergence results are obtained using the standard -norm. Finally, the effectiveness of the proposed method is demonstrated
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Analyzing single cell RNA sequencing with topological nonnegative matrix factorization J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-19 Yuta Hozumi, Guo-Wei Wei
Single-cell RNA sequencing (scRNA-seq) is a relatively new technology that has stimulated enormous interest in statistics, data science, and computational biology due to the high dimensionality, complexity, and large scale associated with scRNA-seq data. Nonnegative matrix factorization (NMF) offers a unique approach due to its meta-gene interpretation of resulting low-dimensional components. However
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The boundary element method for acoustic transmission with nonconforming grids J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-17 Elwin van ’t Wout
Acoustic wave propagation through a homogeneous material embedded in an unbounded medium can be formulated as a boundary integral equation and accurately solved with the boundary element method. The computational efficiency deteriorates at high frequencies due to the increase in mesh size with a fixed number of elements per wavelength and also at high material contrasts due to the ill-conditioning
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Improved bounds on tails of convolutions of compound distributions: Application to ruin probabilities for the risk process perturbed by diffusion J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-15 Stathis Chadjiconstantinidis, Panos Xenos
In this paper we examine the convolution of a compound distribution with another given distribution. For this, new general upper and lower bounds on the tail probabilities of the convolution of a compound geometric distribution are derived. Also, such bounds are obtained under the truncated Cramér-Lundberg condition for the heavy-tailed case. Applications to the ruin probabilities of compound Poisson
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Hermite, Higher order Hermite, Laguerre type polynomials and Burgers like equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-13 Giuseppe Dattoli, Roberto Garra, Silvia Licciardi
The multivariable version of ordinary and generalized Hermite polynomials are the natural solutions of the classical heat equation and of its higher order versions. We derive the associated Burgers equations and show that analogous non-linear partial differential equations can be derived for Laguerre polynomials. The starting point of this extension is the Laguerre diffusive equation, whose non linear
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A strain gradient problem with a fourth-order thermal law J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-13 N. Bazarra, J.R. Fernández, R. Quintanilla
In this paper, a strain gradient thermoelastic problem is studied from the numerical point of view. The heat conduction is modeled by using the type II thermal law and the second gradient of the thermal displacement is also included in the set of independent constitutive variables. An existence and uniqueness result is recalled. Then, the fully discrete approximations are introduced by using the implicit
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A posteriori error estimates of the weak Galerkin finite element methods for parabolic problems J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-13 Jiajia Dai, Luoping Chen, Miao Yang
In this paper, We propose the residual-based a posteriori error estimator of the weak Galerkin finite element method with the backward Euler time discretization for the linear parabolic partial differential equation. For the a posteriori error estimator, we introduce the Helmholtz decomposition technique to prove its reliability. We mainly study WG element . Numerical experiments based on the lowest
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Fully decoupled and high-order linearly implicit energy-preserving RK-GSAV methods for the coupled nonlinear wave equation J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-12 Dongdong Hu
This paper is concerned with high-order accurate, linearly implicit and energy-preserving schemes for the coupled nonlinear wave equation. To this end, a novel auxiliary variable approach proposed in a recent paper (Ju et al., 2022) is applied to reformulate the governing equation in an equivalent system, which possesses a modified energy that consists of primary functional and quadratic functional
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Some new bounds for the blow-up time of solutions for certain nonlinear Volterra integral equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-12 Steven G. From
In this paper, some new upper and lower bounds on the blow-up time of a certain class of nonlinear Volterra integral equations are presented and compared to previously proposed bounds. In most cases, the new bounds are a significant improvement on previously proposed bounds. We present many new bounds, with varying degrees of accuracy and computational complexity. The derivation of the upper bounds
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Generalized weak Galerkin finite element methods for second order elliptic problems J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-10 Dan Li, Chunmei Wang, Junping Wang, Xiu Ye
This article proposes and analyzes the generalized weak Galerkin (gWG) finite element method for the second order elliptic problem. A generalized discrete weak gradient operator is introduced in the weak Galerkin framework so that the gWG methods would not only allow arbitrary combinations of piecewise polynomials defined in the interior and on the boundary of each local finite element, but also work
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The Carleman-Newton method to globally reconstruct the initial condition for nonlinear parabolic equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-10 Anuj Abhishek, Thuy T. Le, Loc H. Nguyen, Taufiquar Khan
We propose to combine the Carleman estimate and the Newton method to solve an inverse problem for nonlinear parabolic equations from lateral boundary data. The stability of this inverse problem for determination of initial condition is conditionally logarithmic. Hence, numerical results due to the conventional least squares optimization might not be reliable. In order to enhance the stability, we approximate
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Local randomized neural networks with discontinuous Galerkin methods for partial differential equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-10 Jingbo Sun, Suchuan Dong, Fei Wang
Randomized Neural Networks (RNNs) are a variety of neural networks in which the hidden-layer parameters are fixed to randomly assigned values, and the output-layer parameters are obtained by solving a linear system through least squares. This improves the efficiency without degrading the accuracy of the neural network. In this paper, we combine the idea of the Local RNN (LRNN) and the Discontinuous
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Physical feature preserving and unconditionally stable SAV fully discrete finite element schemes for incompressible flows with variable density J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-09 Yuyu He, Hongtao Chen, Hang Chen
In this paper, we construct new positive preserving, unconditionally stable and fully discrete finite element schemes for incompressible flows with variable density. The proposed schemes employ the positive function transform for the density equation and scalar auxiliary variable (SAV) for the momentum equation in its reformulation system. The SAV schemes are unconditionally energy stable and second-order
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A Petrov–Galerkin immersed finite element method for steady Navier–Stokes interface problem with non-homogeneous jump conditions J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-09 Na Zhu, Hongxing Rui
This paper develops a lowest-order Petrov–Galerkin immersed method for solving Stokes interface problem. We make use of a uniform, interface-unfitted Cartesian mesh. An immersed Petrov–Galerkin formulation is presented, where the test spaces are conventional finite element spaces and the solution spaces satisfying the jump conditions. For the Stokes and Navier–Stokes interface problem, simple stabilized
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Recent advances in the numerical solution of the Nonlinear Schrödinger Equation J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-09 Luigi Barletti, Luigi Brugnano, Gianmarco Gurioli, Felice Iavernaro
In this review we collect some recent achievements in the accurate and efficient solution of the Nonlinear Schrödinger Equation (NLSE), with the preservation of its Hamiltonian structure. This is achieved by using the energy-conserving Runge–Kutta methods named Hamiltonian Boundary Value Methods (HBVMs) after a proper space semi-discretization. The main facts about HBVMs, along with their application
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Optimal precedence tests under single and double-sampling framework J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-08 Niladri Chakraborty, Narayanaswamy Balakrishnan, Maxim Finkelstein
The precedence test is a nonparametric, two-sample test for stochastic comparison of lifetime data. The power of the precedence test increases with increasing sample size. However, the power curve of the precedence test follows a concave pattern that says the rate of increase in power decreases with increasing sample size. In this article, we intend to find the optimal sample size for the precedence
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A CutFE-LOD method for the multiscale elliptic problems on complex domains J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-08 Kuokuo Zhang, Weibing Deng, Haijun Wu
In this paper, we construct a new combined multiscale finite element method to solve the elliptic problem which has both a highly oscillating diffusion coefficient and a very complicated boundary. To design a numerical method for this kind of problems is difficult because that the microscopically geometrical information of the boundary and oscillation information of the coefficient should be taken
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Optimal error analysis of an unconditionally stable BDF2 finite element approximation for the 3D incompressible MHD equations with variable density J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-07 Shiren Li, Yuan Li
This paper presents a second-order finite element scheme for the approximations of the three-dimensional (3D) incompressible magnetohydrodynamics system with variable density (VD-MHD), where two-step backward differentiation formula (BDF2) is used to discrete the time derivative and the finite elements are used to approximate the density, velocity, pressure and magnetic. Based on an equivalent VD-MHD
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A weak Galerkin meshless method for incompressible Navier–Stokes equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-07 Xiaolin Li
A weak Galerkin meshless (WGM) method is proposed and analyzed in this paper for the incompressible stationary Navier–Stokes equations. In Galerkin meshless methods, we have to deal with the integration of non-polynomial functions, and then the often-used high-order Gauss quadrature rules not only lead to high computational cost but also seriously damage the optimal convergence. In the WGM method,
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Learning computational upscaling models for a class of convection–diffusion equations J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-07 Tsz Fung Yu, Eric T. Chung, Ka Chun Cheung, Lina Zhao
In this paper, we develop a nonlinear upscaling method for the nonlinear convection–diffusion equation based on a carefully designed deep learning framework. The proposed scheme solves the equation on a coarse grid with the cell average as the solution obtained from finite volume method. A local downscaling operator is constructed in order to compute the parameters in the coarse scale equation. This
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A pressure-robust numerical scheme for the Stokes equations based on the WOPSIP DG approach J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-07 Yuping Zeng, Liuqiang Zhong, Feng Wang, Shangyou Zhang, Mingchao Cai
In this paper, we propose and analyze a new weakly over-penalized symmetric interior penalty (WOPSIP) discontinuous Galerkin (DG) scheme for the Stokes equations. The primary approach involves modifying the right-hand term and replacing the pressure-velocity coupling term by incorporating a weak divergence instead of the divergence operator. These modifications allow for pressure-robustness in the
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Statistical Inference for Generalized Power-Law Process in repairable systems J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-06 Tito Lopes, Vera L.D. Tomazella, Jeremias Leão, Pedro L. Ramos, Francisco Louzada
Repairable systems are often used to model the reliability of restored components after a failure is observed. Among various reliability growth models, the power law process (PLP) or Weibull process has been widely used in industrial problems and applications. In this article, we propose a new class of model called the generalized PLP (GPLP), based on change points. These can be treated as known or
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Special issue on advances in quadrature, cubature, and the solution of integral equations with applications J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-06 Luisa Fermo, Gradimir V. Milovanović, Lothar Reichel, Miodrag M. Spalević
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A high-order scheme for mean field games J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-03 Elisa Calzola, Elisabetta Carlini, Francisco J. Silva
In this paper we propose a high-order numerical scheme for time-dependent mean field games systems. The scheme, which is built by combining Lagrange–Galerkin and semi-Lagrangian techniques, is consistent and stable for large time steps compared with the space steps. We provide a convergence analysis for the exactly integrated Lagrange–Galerkin scheme applied to the Fokker–Planck equation, and we propose
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On strong convergence of two numerical methods for singular initial value problems with multiplicative white noise J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-03 Nan Deng, Wanrong Cao
Mean-square convergence of the Milstein method and the Euler–Maruyama (EM) method are investigated for stochastic singular initial value problems (SIVPs) driven by multiplicative white noise. For the first-order model equation, the existence, uniqueness, and moment boundedness of the exact solution are developed under some appropriate assumptions. On this basis, it is proved that the Milstein method
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A discrete model for force-based elasticity and plasticity J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-01-29 Ioannis Dassios, Georgios Tzounas, Federico Milano, Andrey Jivkov
The article presents a mathematical model that simulates the elastic and plastic behaviour of discrete systems representing isotropic materials. The systems consist of one lattice of nodes connected by edges and a second lattice with nodes placed at the centres of the existing edges. The derivation is based on the assumption that the kinematics of the second lattice is induced by the kinematics of
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A class of reducible quadrature rules for the second-kind Volterra integral equations using barycentric rational interpolation J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-02 Junjie Ma
Reducible quadrature rules constitute a well-established class of direct quadrature methods for approximating solutions to Volterra integral equations. Unlike interpolatory quadrature formulae, the reducible quadrature rule can be constructed without the need for additional calculations of moments. This paper investigates the reducible quadrature rule by employing barycentric rational interpolation
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Rapidly convergent series and closed-form expressions for a class of integrals involving products of spherical Bessel functions J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-02 Giampiero Lovat, Salvatore Celozzi
Rapidly convergent series are derived to efficiently evaluate a class of integrals involving the product of spherical Bessel functions of the first kind occurring in acoustic and electromagnetic scattering from circular disks and apertures. Depending on the involved parameters, the series can be further reduced to closed-form expressions in terms of generalized hypergeometric functions or Meijer G-functions
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Multilevel Schoenberg-Marsden variation diminishing operator and related quadratures J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-02 Elena Fornaca, Paola Lamberti
In this paper we propose an improvement of the classical Schoenberg-Marsden variation diminishing operator with applications to the construction of new quadrature rules that we show having better performances with respect to the already known ones based on the classical cited operator. We discuss convergence properties and error estimates. Numerical experiments are also carried out to confirm the presented
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Prediction of future observations based on ordered extreme k-records ranked set sampling with unequal fixed and random sample sizes J. Comput. Appl. Math. (IF 2.4) Pub Date : 2024-02-02 Haidy A. Newer
The construction of prediction intervals for future Rayleigh observations in the context of ordered extreme k-record ranked set sampling based on unequal random and non-random sample sizes is proposed in this study using two pivotal statistics. The distribution functions of the pivotal statistics are obtained in explicit form. Certain cases for the random sample size are analysed. Moreover, a simulation