Linear Multistep Method for Advanced IDEs with Piecewise Constant Arguments

In this article, based on the linear multistep method, we combined the simplified reproducing kernel method (SRKM) with the optimization method to solve advanced IDEs with piecewise constant arguments. This article also discussed the convergence order and the time complexity of the method. It is pro...

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Bibliographic Details
Main Authors: Liangcai Mei, Boying Wu, Yingzhen Lin
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2022/6191276
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Summary:In this article, based on the linear multistep method, we combined the simplified reproducing kernel method (SRKM) with the optimization method to solve advanced IDEs with piecewise constant arguments. This article also discussed the convergence order and the time complexity of the method. It is proved that the approximate solutions and their derivatives obtained by this algorithm are uniformly convergent. Through two numerical examples, it is proved that the proposed algorithm is obviously better than other methods.
ISSN:2314-4785