Geodesic
Comparative analysis of algorithms for estimating fish population dynamics
Diskretnyj analiz i issledovanie operacij, Tome 31 (2024) no. 2, pp. 80-95 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

The aim of the present work is to create a tool for comparing algorithms for estimating the dynamics of the abundance of individual fish species in Lake Baikal based on experimental catching. For each instance of a randomly selected fish, its age is determined using a special technology. From the obtained data on the numbers of fish of different ages in the sample, the parameters of the given laws of age distribution are estimated. This serves as a basis for the formation of ideas about the dynamics of mortality and changes in the abundance of fish of this species in previous years. Various algorithms can be used to estimate the parameters of distribution laws, sometimes leading to considerably different results. The discussed technique for comparing parameter estimation algorithms is based on multiple computational experiments using the Monte Carlo method to simulate random samples of fish. The proposed method analyzes several algorithms for estimating the parameters of a truncated exponential distribution law for different sample sizes. As an example, the problem of estimating the mortality dynamics of the Baikal oilfish (Comephorus), the major biomass fish of Lake Baikal, is considered. Illustr. 4, bibliogr. 13.
Keywords: estimation of fish mortality parameters, Lake Baikal, comephorus, truncated exponential distribution law, method of statistical testing. 
@article{DA_2024_31_2_a4,
     author = {V. I. Zorkaltsev and A. S. Knyazev},
     title = {Comparative analysis of algorithms for~estimating fish population dynamics},
     journal = {Diskretnyj analiz i issledovanie operacij},
     pages = {80--95},
     year = {2024},
     volume = {31},
     number = {2},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/DA_2024_31_2_a4/}
}
TY  - JOUR
AU  - V. I. Zorkaltsev
AU  - A. S. Knyazev
TI  - Comparative analysis of algorithms for estimating fish population dynamics
JO  - Diskretnyj analiz i issledovanie operacij
PY  - 2024
SP  - 80
EP  - 95
VL  - 31
IS  - 2
UR  - http://geodesic.mathdoc.fr/item/DA_2024_31_2_a4/
LA  - ru
ID  - DA_2024_31_2_a4
ER  - 
%0 Journal Article
%A V. I. Zorkaltsev
%A A. S. Knyazev
%T Comparative analysis of algorithms for estimating fish population dynamics
%J Diskretnyj analiz i issledovanie operacij
%D 2024
%P 80-95
%V 31
%N 2
%U http://geodesic.mathdoc.fr/item/DA_2024_31_2_a4/
%G ru
%F DA_2024_31_2_a4
V. I. Zorkaltsev; A. S. Knyazev. Comparative analysis of algorithms for estimating fish population dynamics. Diskretnyj analiz i issledovanie operacij, Tome 31 (2024) no. 2, pp. 80-95. http://geodesic.mathdoc.fr/item/DA_2024_31_2_a4/

[1] A. I. Kobzar', Applied Mathematical Statistics, Fizmatlit, M., 2012 (Russian)

[2] E. A. Trofimova, N. V. Kislyak, and D. V. Gilyov, Probability Theory and Mathematical Statistics, Izd. Ural. Univ., Yekaterinburg, 2018 (Russian)

[3] M. V. Kozlov and A. K. Prokhorov, Introduction to Mathematical Statistics, MGU, M., 1987 (Russian) | MR

[4] K. F. Gauss, Selected Geodesic Works, v. 1, Geodezizdat, M., 1957 (Russian)

[5] V. I. Zorkaltsev and A. S. Knyazev, “Comparative analysis of methods for assessing the dynamics of fish mortality in Lake Baikal based on computational experiments”, Computation Technologies and Applied Mathematics, Proc. 2nd Int. Semin. (Blagoveshchensk, Russia, June 12–16, 2023), Izd. Amur. Gos. Univ., Blagoveshchensk, 2023, 91–94 (Russian)

[6] V. I. Zorkaltsev, Elements of Optimization Theory, ISEhM SO RAN, Irkutsk, 2014 (Russian)

[7] G. V. Starikov, Golomyankas of The Baikal, Nauka, Novosibirsk, 1977 (Russian)

[8] A. V. Sokolov, V. A. Petekrfeld, A. I. Bobkov, et al., “The Baikal omul”, Proceedings Justifying the Total Allowable Catches of Aquatic Biological Resources in Lake Baikal for 2018, VNIRO, M., 2017, 5–24 (Russian)

[9] V. V. Kafanova, Methods for Determining the Age and Growth of Fish, Izd. Tomsk. Univ., Tomsk, 1984 (Russian)

[10] I. V. Bychkov, V. I. Zorkaltsev, and A. V. Kazazaeva, “Weight coefficients in the weighted least squares method”, Numer. Anal. Appl., 18:3 (2015), 223–234 | DOI | MR | MR | Zbl

[11] I. V. Bychkov, V. I. Zorkaltsev, and I. V. Mokryi, “Estimates of parameters for the truncated exponential law of distribution on the basis of exponential data”, Vychisl. Tekhnol., 23:5 (2018), 3–20 (Russian) | DOI | MR

[12] P. N. Anoshko, Eh. L. Afanasyeva, E. V. Dzyuba, et al., Formation of a system of models for trophic relationships in the pelagic ecosystem of Lake Baikal, Prepr. No 11, ISEhM SO RAN, Irkutsk, 1998 (Russian)

[13] V. I. Zorkaltsev, I. V. Mokryi, and A. V. Kazazaeva, “Modeling the pelagic community of Lake Baikal ecosystem”, Vychisl. Tekhnol., 16:1 (2011), 48–60 (Russian) | MR