Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application

The Lotka–Volterra model is widely applied in various fields, and parameter estimation is important in its application. In this study, the Lotka–Volterra model with universal applicability is established by introducing the fractional order. Modulation function is multiplied by both sides of the Lotk...

Full description

Bibliographic Details
Main Authors: Ying Hao, Mingshun Guo
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2021/6645059
id doaj-78054145f7c14a6787634f35739e7129
record_format Article
spelling doaj-78054145f7c14a6787634f35739e71292021-07-26T00:35:04ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/6645059Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its ApplicationYing Hao0Mingshun Guo1School of ManagementSchool of ManagementThe Lotka–Volterra model is widely applied in various fields, and parameter estimation is important in its application. In this study, the Lotka–Volterra model with universal applicability is established by introducing the fractional order. Modulation function is multiplied by both sides of the Lotka–Volterra model, and the model is converted into linear equations with parameters to be estimated by the fractional integration method. The parameters are obtained by solving the equations. The state of the system is estimated by shifted Chebyshev polynomial. Last, the implementation program of the model is compiled. The concrete implementation method of the improved model is proposed by an example in this study.http://dx.doi.org/10.1155/2021/6645059
collection DOAJ
language English
format Article
sources DOAJ
author Ying Hao
Mingshun Guo
spellingShingle Ying Hao
Mingshun Guo
Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
Mathematical Problems in Engineering
author_facet Ying Hao
Mingshun Guo
author_sort Ying Hao
title Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
title_short Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
title_full Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
title_fullStr Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
title_full_unstemmed Parameter Estimation of the Lotka–Volterra Model with Fractional Order Based on the Modulation Function and Its Application
title_sort parameter estimation of the lotka–volterra model with fractional order based on the modulation function and its application
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1563-5147
publishDate 2021-01-01
description The Lotka–Volterra model is widely applied in various fields, and parameter estimation is important in its application. In this study, the Lotka–Volterra model with universal applicability is established by introducing the fractional order. Modulation function is multiplied by both sides of the Lotka–Volterra model, and the model is converted into linear equations with parameters to be estimated by the fractional integration method. The parameters are obtained by solving the equations. The state of the system is estimated by shifted Chebyshev polynomial. Last, the implementation program of the model is compiled. The concrete implementation method of the improved model is proposed by an example in this study.
url http://dx.doi.org/10.1155/2021/6645059
work_keys_str_mv AT yinghao parameterestimationofthelotkavolterramodelwithfractionalorderbasedonthemodulationfunctionanditsapplication
AT mingshunguo parameterestimationofthelotkavolterramodelwithfractionalorderbasedonthemodulationfunctionanditsapplication
_version_ 1721282333172039680