Authentication email has already been sent, please check your email box: and activate it as soon as possible.
You can login to My Profile and manage your email alerts.
If you haven’t received the email, please:
|
|
There are 1 papers published in subject: > since this site started. |
Results per page: |
Select Subject |
Select/Unselect all | For Selected Papers |
Saved Papers
Please enter a name for this paper to be shown in your personalized Saved Papers list
|
1. Feedforward neural network with Reformulated Levenberg-Marquardt optimization algorithm for solving ordinary differential equations | |||
Li Shangjie,Li Haibin,He Yun | |||
Mechanics 10 July 2018 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:This paper reformulates Levenberg-Marquardt (RLM) training algorithm in neural networks for solving ordinary differential equations (ODEs), and multiple joint training LM (MJLM) algorithm is proposed for solving coupled ODEs. However, there are several new approaches in literature to solve ODEs, but the new approach has more advantages, such as fast convergence and also little error. The optimal values for the corresponding adjustable parameters are calculated, an accurate approximate solution is obtained, which works well for interior and exterior points of the original domain. We show how to apply this method to a specific example of ODEs, the accuracy of the method is illustrated by solving several problems. | |||
TO cite this article:Li Shangjie,Li Haibin,He Yun. Feedforward neural network with Reformulated Levenberg-Marquardt optimization algorithm for solving ordinary differential equations[OL].[10 July 2018] http://en.paper.edu.cn/en_releasepaper/content/4745699 |
Select/Unselect all | For Selected Papers |
Saved Papers
Please enter a name for this paper to be shown in your personalized Saved Papers list
|
Results per page: |
About Sciencepaper Online | Privacy Policy | Terms & Conditions | Contact Us
© 2003-2012 Sciencepaper Online. unless otherwise stated