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Some Remarks on a Variational Method for Stiff Differential Equations [PDF]
Mathematics, 2019 We have recently proposed a variational framework for the approximation of systems of differential equations. We associated, in a natural way, with the original problem, a certain error functional. The discretization is based on standard descent schemes,
Sergio Amat +2 more
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Stiff neural ordinary differential equations [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Neural Ordinary Differential Equations (ODEs) are a promising approach to learn dynamical models from time-series data in science and engineering applications. This work aims at learning neural ODEs for stiff systems, which are usually raised from chemical kinetic modeling in chemical and biological systems.
Suyong Kim +4 more
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Haar wavelet collocation method for linear first order stiff differential equations [PDF]
ITM Web of Conferences, 2020 In general, there are countless types of problems encountered from different disciplines that can be represented by differential equations. These problems can be solved analytically in simpler cases; however, computational procedures are required for more ...
Atay Mehmet Tarık +4 more
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Mendel, 2022 This paper examines the implementation of simple combination mutation of differential evolution algorithm for solving stiff ordinary differential equations.
Werry Febrianti +2 more
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Exponential Multistep Methods for Stiff Delay Differential Equations
Axioms, 2022 Stiff delay differential equations are frequently utilized in practice, but their numerical simulations are difficult due to the complicated interaction between the stiff and delay terms.
Rui Zhan +3 more
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Optimizing the Coefficients of Numerical Differentiation Formulae Using Neural Networks
IEEE Access, 2021 The use of a numerical differentiation formula (NDF) is an excellent method for solving stiff ordinary differential equations. However, the NDF method cannot fully adapt to all stiff systems.
Xinyu Yang +3 more
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Schur Decomposition for Stiff Differential Equations
CoRR, 2023 A quantitative definition of numerical stiffness for initial value problems is proposed. Exponential integrators can effectively integrate linearly stiff systems, but they become expensive when the linear coefficient is a matrix, especially when the time step is adapted to maintain a prescribed local error.
Thoma Zoto, John C. Bowman
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IEEE Access, 2022 The modeling and simulation of fluid power systems are essential parts of the real-time simulation of virtual prototypes of mobile working machines.
Stanislav Ustinov +2 more
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Solutions of Stiff Systems of Ordinary Differential Equations Using Residual Power Series Method
Journal of Mathematics, 2022 The stiff differential equations occur in almost every field of science. These systems encounter in mathematical biology, chemical reactions and diffusion process, electrical circuits, meteorology, mechanics, and vibrations. Analyzing and predicting such
Mubashir Qayyum, Qursam Fatima
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An approximate numerical solution of some of the stiff linear boundary values problems of the second order using the method of matching with multiple shooting and interpolation. [PDF]
مجلة التربية والعلم, 2009 The purpose of this research combining the algorithm of superposition with multiple shooting and interpolation designing for solving Stiff linear boundary value problems in ordinary differential equations.
Mohammed Altai, Suhaib Abdulbaqi
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