A parameter identification problem for the mathematical model of HIV dynamics

Sergey Kabanikhin; Olga Krivorotko; Darya Yermolenko

doi:10.1109/SIBIRCON.2017.8109842

A parameter identification problem for the mathematical model of HIV dynamics

Sergey Kabanikhin, Olga Krivorotko, Darya Yermolenko

Механико-математический факультет

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › рецензирование

Аннотация

In this paper, a problem of specifying HIV-infection parameters and immune response using additional measurements of the concentrations of the T-lymphocytes, the free virus, and the immune effectors at fixed times for a mathematical model of HIV dynamics is investigated numerically. The problem of specifying the parameters of the mathematical model (an inverse problem) is reduced to a problem of minimizing an objective function describing the deviation of the simulation results from the experimental data. A genetic algorithm for solving the least squares function minimization problem method is implemented and investigated. The results of a numerical solution of the inverse problem are analyzed.

Язык оригинала	английский
Название основной публикации	Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
Издатель	Institute of Electrical and Electronics Engineers Inc.
Страницы	82-86
Число страниц	5
ISBN (электронное издание)	9781538615966
DOI	https://doi.org/10.1109/SIBIRCON.2017.8109842
Состояние	Опубликовано - 14 ноя 2017
Событие	2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 - Novosibirsk, Российская Федерация Продолжительность: 18 сен 2017 → 22 сен 2017

Конференция

Конференция	2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
Страна	Российская Федерация
Город	Novosibirsk
Период	18.09.2017 → 22.09.2017

Доступ к документу

10.1109/SIBIRCON.2017.8109842

Link to publication in Scopus

Fingerprint Подробные сведения о темах исследования «A parameter identification problem for the mathematical model of HIV dynamics». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать

Kabanikhin, S., Krivorotko, O., & Yermolenko, D. (2017). A parameter identification problem for the mathematical model of HIV dynamics. В Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 (стр. 82-86). [8109842] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON.2017.8109842

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title = "A parameter identification problem for the mathematical model of HIV dynamics",

abstract = "In this paper, a problem of specifying HIV-infection parameters and immune response using additional measurements of the concentrations of the T-lymphocytes, the free virus, and the immune effectors at fixed times for a mathematical model of HIV dynamics is investigated numerically. The problem of specifying the parameters of the mathematical model (an inverse problem) is reduced to a problem of minimizing an objective function describing the deviation of the simulation results from the experimental data. A genetic algorithm for solving the least squares function minimization problem method is implemented and investigated. The results of a numerical solution of the inverse problem are analyzed.",

keywords = "Genetic algorithm, Inverse problem, Least square method, Mathematical model of HIV dynamics",

author = "Sergey Kabanikhin and Olga Krivorotko and Darya Yermolenko",

year = "2017",

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day = "14",

doi = "10.1109/SIBIRCON.2017.8109842",

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booktitle = "Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 ; Conference date: 18-09-2017 Through 22-09-2017",

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Kabanikhin, S, Krivorotko, O & Yermolenko, D 2017, A parameter identification problem for the mathematical model of HIV dynamics. в Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017., 8109842, Institute of Electrical and Electronics Engineers Inc., стр. 82-86, 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017, Novosibirsk, Российская Федерация, 18.09.2017. https://doi.org/10.1109/SIBIRCON.2017.8109842

A parameter identification problem for the mathematical model of HIV dynamics. / Kabanikhin, Sergey; Krivorotko, Olga; Yermolenko, Darya.

Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 82-86 8109842.

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › рецензирование

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N2 - In this paper, a problem of specifying HIV-infection parameters and immune response using additional measurements of the concentrations of the T-lymphocytes, the free virus, and the immune effectors at fixed times for a mathematical model of HIV dynamics is investigated numerically. The problem of specifying the parameters of the mathematical model (an inverse problem) is reduced to a problem of minimizing an objective function describing the deviation of the simulation results from the experimental data. A genetic algorithm for solving the least squares function minimization problem method is implemented and investigated. The results of a numerical solution of the inverse problem are analyzed.

AB - In this paper, a problem of specifying HIV-infection parameters and immune response using additional measurements of the concentrations of the T-lymphocytes, the free virus, and the immune effectors at fixed times for a mathematical model of HIV dynamics is investigated numerically. The problem of specifying the parameters of the mathematical model (an inverse problem) is reduced to a problem of minimizing an objective function describing the deviation of the simulation results from the experimental data. A genetic algorithm for solving the least squares function minimization problem method is implemented and investigated. The results of a numerical solution of the inverse problem are analyzed.

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