tinroИзвестия ТИНРОIzvestiya TINRO1606-99192658-5510ТИНРО10.26428/1606-9919-2022-202-601-622tinro-758Research ArticleБИОЛОГИЧЕСКИЕ РЕСУРСЫBIOLOGICAL RESOURCESО применении фильтров Калмана в когортных моделяхOn application of Kalman filters in cohort modelshttps://orcid.org/0000-0003-3581-5333ИльинО. И.IlinO. I.

Ильин Олег Игоревич, кандидат физико-математических наук, ведущий научный сотрудник

683000, г. Петропавловск-Камчатский, ул. Набережная, 18

Oleg I. Ilin, Ph.D., leading researcher

18, Naberezhnaya Street, Petropavlovsk-Kamchatsky, 683000

ilin.o.i@kamniro.ruКамчатский филиал ВНИРО (КамчатНИРО)РоссияKamchatka branch of VNIRO (KamchatNIRO)Russian Federation2022041020222023601622Copyright © Ильин О.И., 20222022Ильин О.И.Ilin O.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://izvestiya.tinro-center.ru/jour/article/view/758

На примере восточнокамчатского минтая рассматривается один из возможных подходов к оценке состояния запасов морских промысловых гидробионтов по данным о возрастной структуре уловов. Представлены алгоритмы субоптимальной фильтрации и интерполяции (сглаживающий расширенный фильтр Калмана и сглаживающий сигма-точечный фильтр Калмана) для когортной модели эксплуатируемого запаса при наличии неопределенности относительно истинного значения вектора параметров системы.

On example of walleye pollock at East Kamchatka, one of possible approaches is considered to assess the state of stocks for marine commercial species with usage of the data on age structure in catches. Algorithms for suboptimal filtering and interpolation (extended Kalman smoother and unscented Kalman smoother) are presented for a cohort model of an exploited stock, in presence of uncertainty about true value of the vector of the system parameters.

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The authors declare that there are no conflicts of interest present.