Results 31 to 40 of about 2,763,547 (281)

SOLUSI DARI PERSAMAAN CAUCHY–EULER NONHOMOGEN KASUS LOGARITMIK

open access: yesE-Jurnal Matematika, 2020
Ordinary differential equation is one form of differential equations that are often found in everyday life. One form of ordinary differential equations which has non–constant coefficients is the Cauchy–Euler differential equation.
I GEDE PUTU MIKI SUKADANA   +2 more
doaj   +1 more source

Fault Diagnosis via Neural Ordinary Differential Equations

open access: yesApplied Sciences, 2021
Implementation of model-based fault diagnosis systems can be a difficult task due to the complex dynamics of most systems, an appealing alternative to avoiding modeling is to use machine learning-based techniques for which the implementation is more ...
Luis Enciso-Salas   +2 more
doaj   +1 more source

Neural Ordinary Differential Equations

open access: yesCoRR, 2018
We introduce a new family of deep neural network models. Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network. The output of the network is computed using a black-box differential equation solver.
Tian Qi Chen   +3 more
openaire   +3 more sources

Predicting Ordinary Differential Equations with Transformers

open access: yesCoRR, 2023
We develop a transformer-based sequence-to-sequence model that recovers scalar ordinary differential equations (ODEs) in symbolic form from irregularly sampled and noisy observations of a single solution trajectory. We demonstrate in extensive empirical evaluations that our model performs better or on par with existing methods in terms of accurate ...
Becker, S.   +4 more
openaire   +6 more sources

Backward difference replacements of the space derivative in first order hyperbolic equations [PDF]

open access: yes, 1983
Two families of two-time level difference schemes are developed for the numerical solution of first order hyperbolic partial differential equations with one space variable.
Khaliq, AQM, Twizell, EH
core   +4 more sources

Lipschitz stability for generalized ordinary differential equations and impulsive retarded differential equations

open access: yesElectronic Journal of Qualitative Theory of Differential Equations, 2019
We consider a class of retarded functional differential equations with preassigned moments of impulsive effect and we study the Lipschitz stability of solutions of these equations using the theory of generalized ordinary differential equations and ...
Suzete Afonso, Márcia da Silva
doaj   +1 more source

Characteristic Neural Ordinary Differential Equations

open access: yesCoRR, 2021
We propose Characteristic-Neural Ordinary Differential Equations (C-NODEs), a framework for extending Neural Ordinary Differential Equations (NODEs) beyond ODEs. While NODEs model the evolution of a latent variables as the solution to an ODE, C-NODE models the evolution of the latent variables as the solution of a family of first-order quasi-linear ...
Xingzi Xu   +4 more
openaire   +3 more sources

On the solutions of fractional random ordinary differential equations with the Residual power series method

open access: yesAlexandria Engineering Journal, 2023
In this study, random ordinary differential equations obtained by randomly choosing the coefficients or initial conditions of the ordinary differential equations will be analyzed by the Residual Power Series Method. The initial conditions or coefficients
Mehmet Merdan, Nihal Atasoy
doaj   +1 more source

Adomian Decomposition Method to Solve the Second Order Ordinary Differential Equations with Constant Coefficient

open access: yes, 2023
: In this paper, we will display Adomian decomposition method for solving second-order ordinary differential equations with constant coefficient. The Adomian decomposition method(ADM) is a creative and effective method for exact solution. It is important
Mohammed Ali Qasem Mohsen   +1 more
core   +1 more source

Solve the Second Order Ordinary Differential Equations by Adomian Decomposition Method

open access: yes, 2023
: The Adomian decomposition model (ADM) is described by Evans and Raslan (2005) as a semi-analytical model used to solve partial and ordinary non-linear differentials.
Yousef Ali Sulaiman Alsulaiman   +1 more
core   +1 more source

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