English
Related papers

Related papers: Fuzzy general linear methods

200 papers

Advances in deep learning have enabled physics-informed neural networks to solve partial differential equations. Numerical differentiation using the finite-difference (FD) method is efficient in physics-constrained designs, even in…

Machine Learning · Computer Science 2024-12-02 Yiye Zou , Tianyu Li , Lin Lu , Jingyu Wang , Shufan Zou , Laiping Zhang , Xiaogang Deng

We demonstrate the effectiveness of a novel scheme for numerically solving linear differential equations whose solutions exhibit extreme oscillation. We take a standard Runge-Kutta approach, but replace the Taylor expansion formula with a…

Computational Physics · Physics 2016-12-12 W. J. Handley , A. N. Lasenby , M. P. Hobson

In the present work, a multi-scale framework for neural network enhanced methods is proposed for approximation of function and solution of partial differential equations (PDEs). By introducing the multi-scale concept, the total solution of…

Numerical Analysis · Mathematics 2022-09-07 Xiaodan Ren

In this paper, the generalized finite element method (GFEM) for solving second order elliptic equations with rough coefficients is studied. New optimal local approximation spaces for GFEMs based on local eigenvalue problems involving a…

Numerical Analysis · Mathematics 2021-12-22 Chupeng Ma , Robert Scheichl , Tim Dodwell

We discuss a new version of a method for obtaining exact solutions of nonlinear partial differential equations. We call this method the Simple Equations Method (SEsM). The method is based on representation of the searched solution as…

Exactly Solvable and Integrable Systems · Physics 2019-08-21 Nikolay K. Vitanov , Zlatinka I. Dimitrova

Fuzzy Neural Networks (FNNs) are effective machine learning models for classification tasks, commonly based on the Takagi-Sugeno-Kang (TSK) fuzzy system. However, when faced with high-dimensional data, especially with noise, FNNs encounter…

Machine Learning · Computer Science 2024-10-18 Yingtao Ren , Yu-Cheng Chang , Thomas Do , Zehong Cao , Chin-Teng Lin

We develop a family of expanded mixed Multiscale Finite Element Methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed Multiscale Finite Element formulation in the sense…

Numerical Analysis · Mathematics 2012-05-22 Lijian Jiang , Dylan Copeland , J. David Moulton

In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice in many real problems due to the easy understanding of the…

Machine Learning · Computer Science 2015-07-20 I. Rodríguez-Fdez , M. Mucientes , A. Bugarín

This article is meant to give a lucid and widely accessible, self-contained account of a novel way of performing arithmetic operations on fuzzy intervals. Based on two formulae of generalized inversion (the first in close analogy to the…

General Mathematics · Mathematics 2016-10-28 Jan Schneider

We describe a version of the FGLM algorithm that can be used to compute generic fibers of positive-dimensional polynomial ideals. It combines the FGLM algorithm with a Hensel lifting strategy. In analogy with Hensel lifting, we show that…

Symbolic Computation · Computer Science 2024-09-20 Jérémy Berthomieu , Rafael Mohr

In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite…

Numerical Analysis · Mathematics 2015-06-12 Yalchin Efendiev , Juan Galvis , Thomas Y. Hou

A Lagrangian numerical scheme for solving nonlinear degenerate Fokker-Planck equations in space dimensions $d\ge2$ is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies…

Numerical Analysis · Mathematics 2018-06-18 José A. Carrillo , Bertram Düring , Daniel Matthes , David S. McCormick

The Boltzmann equation, as a model equation in statistical mechanics, is used to describe the statistical behavior of a large number of particles driven by the same physics laws. Depending on the media and the particles to be modeled, the…

Numerical Analysis · Mathematics 2019-04-16 Eric Chung , Yalchin Efendiev , Yanbo Li , Qin Li

Fluid dynamic equations are valid in their respective modeling scales. With a variation of the modeling scales, theoretically there should have a continuous spectrum of fluid dynamic equations. In order to study multiscale flow evolution…

Numerical Analysis · Mathematics 2017-12-21 Chang Liu , Kun Xu , Quanhua Sun , Qingdong Cai

Explicit Runge-Kutta schemes with large stable step sizes are developed for integration of high order spectral difference spatial discretization on quadrilateral grids. The new schemes permit an effective time step that is substantially…

Numerical Analysis · Mathematics 2013-07-16 M. Parsani , D. I. Ketcheson , W. Deconinck

In this paper we introduce and study semigroups of operators on spaces of fuzzy-number-valued functions, and various applications to fuzzy differential equations are presented. Starting from the space of fuzzy numbers, many new spaces…

Analysis of PDEs · Mathematics 2013-06-18 Ciprian G. Gal , Sorin G. Gal

Fuzzy partial integro-differential equations have a major role in the fields of science and engineering. In this paper, we propose the solution of fuzzy partial Volterra integro-differential equation with convolution type kernel using fuzzy…

General Mathematics · Mathematics 2014-05-09 Saif Ullah , Muhammad Farooq , Latif Ahmad , Saleem Abdullah

In this paper we consider systems of partial (multidimensional) linear difference equations. Specifically, such systems arise in scientific computing under discretization of linear partial differential equations and in computational high…

Symbolic Computation · Computer Science 2007-05-23 V. P. Gerdt

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) [J. Comput. Phys., Vol. 255, 2013, pp 680-698] originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme…

Numerical Analysis · Mathematics 2016-08-30 Giacomo Dimarco , Raphaël Loubère , Jacek Narski , Thomas Rey

This paper considers the strong error analysis of the Euler and fast Euler methods for nonlinear overdamped generalized Langevin equations driven by the fractional noise. The main difficulty lies in handling the interaction between the…

Numerical Analysis · Mathematics 2023-02-21 Xinjie Dai , Jialin Hong , Derui Sheng , Tau Zhou