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Coupled nonlinear system of reaction-diffusion equations describing multi-component (species) interactions with heterogeneous coefficients is considered. Finite volume method based approximation for the space is used to construct…

Numerical Analysis · Mathematics 2022-09-13 Maria Vasilyeva , Alexey Sadovski , D. Palaniappan

In computational engineering, ensuring the integrity and safety of structures in fields such as aerospace and civil engineering relies on accurate stress prediction. However, analytical methods are limited to simple test cases, and…

Computational Engineering, Finance, and Science · Computer Science 2025-10-31 Fabian Key , Lukas Freinberger

We consider the least-squares finite element method (lsfem) for systems of nonlinear ordinary differential equations and establish an optimal error estimate for this method when piecewise linear elements are used. The main assumptions are…

Numerical Analysis · Mathematics 2021-10-01 Matthias Chung , Justin Krueger , Honghu Liu

We look at the number of solutions of an equation of the form f_1*f_2*...*f_k=a in a finite field, where each f_i is a multilinear polynomial. We use two methods to construct a solution of this problem for the cases a=0, a<>0, and we…

Number Theory · Mathematics 2007-05-23 T. Narayaninsamy , D. -J. Mercier , J. -P. Cherdieu

This overview is devoted to splitting methods, a class of numerical integrators intended for differential equations that can be subdivided into different problems easier to solve than the original system. Closely connected with this class…

Numerical Analysis · Mathematics 2024-05-08 Sergio Blanes , Fernando Casas , Ander Murua

Singular stochastic partial differential equations informally refer to the partial differential equations with rough random force that leads to the products in the nonlinear terms becoming ill-defined. Besides the theories of regularity…

Probability · Mathematics 2026-01-16 Hongjie Dong , Kazuo Yamazaki

We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our system returns symbolic expressions that can be interpreted…

Machine Learning · Computer Science 2020-11-16 Maysum Panju , Kourosh Parand , Ali Ghodsi

The method of moments in the context of Nonlinear Schrodinger Equations relies on defining a set of integral quantities, which characterize the solution of this partial differential equation and whose evolution can be obtained from a set of…

Pattern Formation and Solitons · Physics 2007-05-23 Victor M. Perez-Garcia , P. Torres , Gaspar D. Montesinos

Typically, nonlinear Support Vector Machines (SVMs) produce significantly higher classification quality when compared to linear ones but, at the same time, their computational complexity is prohibitive for large-scale datasets: this…

Machine Learning · Computer Science 2021-11-11 S. Cipolla , J. Gondzio

Physically relevant soliton solutions of the resonant nonlinear Schrodinger (RNLS) equation with nontrivial boundary conditions, recently proposed for description of uniaxial waves in a cold collisionless plasma, are considered in the…

Exactly Solvable and Integrable Systems · Physics 2009-11-11 Jyh-Hao Lee , Oktay K. Pashaev

A new method named rational expansion method of exponent function is presented to find exact traveling wave solutions of differential-difference equations. This method generalizes the so-called tanh-method and other similar methods. Some…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Chengshi Liu

We present a brief overview of integrability of nonlinear ordinary and partial differential equations with a focus on the Painleve property: an ODE of second order has the Painleve property if the only movable singularities connected to…

Exactly Solvable and Integrable Systems · Physics 2013-02-05 Zlatinka I. Dimitrova , Kaloyan N. Vitanov

In this paper we study existence, regularity, and approximation of solution to a fractional semilinear elliptic equation of order $s \in (0,1)$. We identify minimal conditions on the nonlinear term and the source which leads to existence of…

Analysis of PDEs · Mathematics 2016-07-27 Harbir Antil , Johannes Pfefferer , Mahamadi Warma

A direct approach to exact solutions of nonlinear partial differential equations is proposed, by using rational function transformations. The new method provides a more systematical and convenient handling of the solution process of…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 Wen-Xiu Ma , Jyh-Hao Lee

In this paper, we focus on the reduced basis methodology in the context of non-linear non-affinely parametrized partial differential equations in which affine decomposition necessary for the reduced basis methodology are not obtained [4,…

Analysis of PDEs · Mathematics 2015-04-24 Cécile Daversin , Christophe Prud'Homme

In this paper, an analytic approximation method for highly nonlinear equations, namely the homotopy analysis method (HAM), is employed to solve some backward stochastic differential equations (BSDEs) and forward-backward stochastic…

Numerical Analysis · Mathematics 2018-01-25 Xiaoxu Zhong , Shijun Liao

We apply the version of the method of simplest equation called modified method of simplest equation for obtaining exact traveling wave solutions of a class of equations that contain as particular case a nonlinear PDE that models shallow…

Exactly Solvable and Integrable Systems · Physics 2017-09-18 Nikolay K. Vitanov , Tsvetelina I. Ivanova

In this article we present some integrability conditions for partial difference equations obtained using the formal symmetries approach. We apply them to find integrable partial difference equations contained in a class of equations…

Exactly Solvable and Integrable Systems · Physics 2015-05-20 D. Levi , R. I. Yamilov

In most introductory numerical analysis textbooks, the treatment of a single nonlinear equation often consists of a collection of all-purpose methods that frequently do not work or are inefficient. These textbooks neglect to teach the…

Numerical Analysis · Mathematics 2022-04-06 Aaron Melman

The random feature method (RFM) has demonstrated great potential in bridging traditional numerical methods and machine learning techniques for solving partial differential equations (PDEs). It retains the advantages of mesh-free approaches…

Numerical Analysis · Mathematics 2025-05-02 Mikhail Kuvakin , Zijian Mei , Jingrun Chen