Error estimation using neural network technique for solving ordinary differential equationsopen access
- Authors
- Nam, H.; Baek, K.R.; Bu, S.
- Issue Date
- 1-Dec-2022
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Keywords
- Deferred correction method; Error correction method; Neural network; Ordinary differential equations
- Citation
- Advances in Continuous and Discrete Models, v.2022, no.1
- Journal Title
- Advances in Continuous and Discrete Models
- Volume
- 2022
- Number
- 1
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/30112
- DOI
- 10.1186/s13662-022-03718-4
- ISSN
- 2731-4235
2731-4235
- Abstract
- In this paper, we present a numerical method to solve ordinary differential equations (ODEs) by using neural network techniques in a deferred correction method framework. Similar to the deferred or error correction techniques, a provisional solution of the ODE is preferentially calculated by any lower-order scheme to satisfy given initial conditions, and the corresponding error is investigated by fully connected neural networks and structured to obtain sufficient magnitude of the error. Numerical examples are illustrated to demonstrate the efficiency of the proposed scheme. © 2022, The Author(s).
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- There are no files associated with this item.
- Appears in
Collections - College of Science and Technology > Department of Computer and Information Communications Engineering > 1. Journal Articles
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