Uncertain Gordon-Schaefer model driven by Liu process

被引：7

作者：

Chen, Dan ^{[1
]}

Liu, Yang ^{[2
]}

机构：

[1] Tsinghua Univ, Dept Math Sci, Beijing 100084, Peoples R China

[2] Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2023年 / 450卷

基金：

中国国家自然科学基金;

关键词：

Uncertainty theory; Liu process; Uncertain differential equation; Gordon -Schaefer model; Parameter estimation;

D O I：

10.1016/j.amc.2023.128011

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The purpose of this paper is to employ an uncertain differential equation to model the fish population. Assume that the dynamic noises are described by Liu process. This paper obtains an uncertain Gordon-Schaefer equation. Then the existence, uniqueness, inverse uncertainty distribution, and stability of the solution of the uncertain Gordon-Schaefer equation are discussed. Next, three applications of the solution are given. Furthermore, the moment estimation is applied to inferring the unknown parameters of the uncertain Gordon-Schaefer model, and a brief study of the halibut population is proposed. Finally, a paradox of the stochastic Gordon-Schaefer model is deduced.(c) 2023 Elsevier Inc. All rights reserved.

引用

页数：16

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