Yuanfu Shao

Prof. Yuanfu Shao

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 February 2010 in Mathematical and Computer Modelling
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Journal Article
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YSYuanfu Shao
Yuanfu Shao

10 November 2018 in Methodology and Computing in Applied Probability
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Journal Article
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ZWZhen Wang
Zhen Wang
LLLi-Wei Liu
Li-Wei Liu
YSYuanfu Shao
Yuanfu Shao
XCXudong Chai
Xudong Chai
BCBaoxian Chang
Baoxian Chang

17 September 2022 in Mathematics
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Journal Article
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YSYuanfu Shao
Yuanfu Shao
WKWeili Kong
Weili Kong
In view of prey’s delayed fear due to predators, delayed predator gestation, and the significance of intra-specific competition between predators when their populations are sufficiently large, a prey–predator population model with a density-dependent functional response is established in a deterministic environment. We research the existence and asymptotic stability of the equilibrium statuses. Then, taking into consideration environmental disturbances, we extend the deterministic model to a stochastic model and research the existence and stationary distributions of stochastic solutions. Finally, we perform some numerical simulations to verify the theoretical results. Numerical examples indicate that fear, delays and environmental disturbance play crucial roles in the system stability of the equilibrium status.


10 December 2011 in Journal of Applied Mathematics and Computing
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Journal Article
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CXChangjin Xu
Changjin Xu
YSYuanfu Shao
Yuanfu Shao

1 January 2023 in AIMS Mathematics
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Journal Article
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PDF file
CCChuanfu Chai
Chuanfu Chai
YSYuanfu Shao
Yuanfu Shao
YWYaping Wang
Yaping Wang
In this paper, we investigate a stochastic prey-predator model with Holling-type IV functional responses, anti-predatory behavior (referring to prey resistance to predator), gestation time delay of prey and Lévy noise. We investigate the existence and uniqueness of global positive solutions through Itô's formulation and Lyapunov's method. We also provide sufficient conditions for the persistence and extinction of prey-predator populations. Additionally, we examine the stability of the system distribution and validate our analytical findings through detailed numerical simulations. Our paper concludes with the implications of our results.