Parameter estimation of an hiv model with mutants using sporadically sampled data

Seok Kyoon Kim; Jung Su Kim; Tae Woong Yoon

doi:10.5302/J.ICROS.2011.17.8.753

Parameter estimation of an hiv model with mutants using sporadically sampled data

Seok Kyoon Kim
, Jung Su Kim
, Tae Woong Yoon^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.

Original language	English
Pages (from-to)	753-759
Number of pages	7
Journal	Journal of Institute of Control, Robotics and Systems
Volume	17
Issue number	8
DOIs	https://doi.org/10.5302/J.ICROS.2011.17.8.753
Publication status	Published - 2011 Aug

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Genetic algorithm
HIV model
Mutant virus
Non-uniformly sampled output data
Parameter estimation

ASJC Scopus subject areas

Software
Control and Systems Engineering
Applied Mathematics

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10.5302/J.ICROS.2011.17.8.753

Cite this

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title = "Parameter estimation of an hiv model with mutants using sporadically sampled data",

abstract = "The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.",

keywords = "Genetic algorithm, HIV model, Mutant virus, Non-uniformly sampled output data, Parameter estimation",

author = "Kim, \{Seok Kyoon\} and Kim, \{Jung Su\} and Yoon, \{Tae Woong\}",

year = "2011",

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language = "English",

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AU - Kim, Seok Kyoon

AU - Kim, Jung Su

AU - Yoon, Tae Woong

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N2 - The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.

AB - The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.

KW - Genetic algorithm

KW - HIV model

KW - Mutant virus

KW - Non-uniformly sampled output data

KW - Parameter estimation

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Parameter estimation of an hiv model with mutants using sporadically sampled data

Abstract

UN SDGs

Keywords

ASJC Scopus subject areas

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