AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (3.6 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Stochastic persistence and global attractivity of a two-predator one-prey system with S-type distributed time delays

Zeyan YueLijuan DongSheng Wang( )
School of Mathematics and Information Science, Henan Polytechnic University, Jiaozuo, Henan 454003, China
Show Author Information

Abstract

In this paper, well-posedness and asymptotic behaviors of a stochastic two-predator one-prey system with S-type distributed time delays are studied by using stochastic analytical techniques. First, the existence and uniqueness of global positive solution with positive initial condition is proved. Second, sufficient conditions for persistence in mean and extinction of each species are obtained. Then, sufficient conditions for global attractivity are established. Finally, some numerical simulations are provided to support the analytical results.

References

【1】
【1】
 
 
Mathematical Modelling and Control
Pages 272-281

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Yue Z, Dong L, Wang S. Stochastic persistence and global attractivity of a two-predator one-prey system with S-type distributed time delays. Mathematical Modelling and Control, 2022, 2(4): 272-281. https://doi.org/10.3934/mmc.2022026

6

Views

0

Downloads

0

Crossref

1

Web of Science

1

Scopus

Received: 14 October 2022
Revised: 25 November 2022
Accepted: 07 December 2022
Published: 15 December 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)