Numerical Modelling of Mean-Field Game Epidemic Научная публикация
| Конференция |
XIV International Conference Optimization and Applications 18-22 сент. 2023 , Петровац, Черногория |
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| Сборник | Optimization and Applications : 14th International Conference, OPTIMA 2023, Petrovac, Montenegro, September 18–22, 2023, Revised Selected Papers Сборник, Springer. 2023. 390 c. ISBN 9783031478598. |
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| Журнал |
Lecture Notes in Computer Science
ISSN: 0302-9743 , E-ISSN: 1611-3349 |
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| Вых. Данные | Год: 2023, Том: 14395, Страницы: 207-217 Страниц : 11 DOI: 10.1007/978-3-031-47859-8_15 | ||||
| Ключевые слова | Mean field game · Kolmogorov-Fokker-Planck · Hamilton-Jacobi-Bellman · Collocation method · SIR model | ||||
| Авторы |
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| Организации |
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Информация о финансировании (2)
| 1 | Российский научный фонд | 23-71-10068 |
| 2 | Математический центр в Академгородке | 075-15-2022-282 |
Реферат:
The mean-field game model of infectious disease local propagation is formulated and solved numerically considering social behavior of modelled population. The numerical algorithm based on collocation method is proposed. As a result of numerical modelling with specific assumptions about population, its movement cost, knowledge about infected group, initial distribution and its optimal behavior is acquired and discussed.
Библиографическая ссылка:
Neverov A.
, Krivorotko O.
Numerical Modelling of Mean-Field Game Epidemic
В сборнике Optimization and Applications : 14th International Conference, OPTIMA 2023, Petrovac, Montenegro, September 18–22, 2023, Revised Selected Papers. – Springer., 2023. – C.207-217. – ISBN 9783031478598. DOI: 10.1007/978-3-031-47859-8_15 Scopus OpenAlex
Numerical Modelling of Mean-Field Game Epidemic
В сборнике Optimization and Applications : 14th International Conference, OPTIMA 2023, Petrovac, Montenegro, September 18–22, 2023, Revised Selected Papers. – Springer., 2023. – C.207-217. – ISBN 9783031478598. DOI: 10.1007/978-3-031-47859-8_15 Scopus OpenAlex
Даты:
| Опубликована в печати: | 10 нояб. 2023 г. |
| Опубликована online: | 10 нояб. 2023 г. |
Идентификаторы БД:
| Scopus: | 2-s2.0-85177210221 |
| OpenAlex: | W4388522868 |