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Recognition of Vertical Migrations for Two Age Groups of Zooplankton

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Mathematical Modeling and Supercomputer Technologies (MMST 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1750))

Abstract

The purpose of the work is to predict the appearance of significant vertical movements of two age zooplankton groups as a result of adaptation to habitat conditions. The methodological basis for solving the problem is the maximization of the fitness function. Vertical migrations are considered as a strategy that ensures the achievement of the greatest value of this function for given environmental conditions. The environmental factors influencing the appearance of vertical migrations are the availability of food and predator activity, water temperature and hydrogen sulfide concentration. Experimentally recorded data on these factors have always some noise and are of a discrete selective nature. In this regard, machine learning tools are used to solve the problem. The most important stage of the work is the construction of the training sample. For this purpose, the results of an analytical and numerical search for the optimal behavior are used with linear-quadratic and hyperbolic approximations of external factors.

As a result of the study, a neural network was built that solves the problem of classifying input data sets into four classes corresponding to the presence or absence of significant vertical movements in young and adult individuals under these conditions. This makes it possible to fairly accurately recognize the presence or absence of significant vertical migrations for young and adult zooplankton individuals according to approximately specified environmental factors.

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Authors and Affiliations

  1. Lobachevsky State University, Gagarin Avenue 23, 603950, Nizhny Novgorod, Russia

    O. Kuzenkov & E. Ryabova

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  1. O. Kuzenkov
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  2. E. Ryabova
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Correspondence to E. Ryabova .

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  1. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia

    Dmitry Balandin

  2. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia

    Konstantin Barkalov

  3. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia

    Iosif Meyerov

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Kuzenkov, O., Ryabova, E. (2022). Recognition of Vertical Migrations for Two Age Groups of Zooplankton. In: Balandin, D., Barkalov, K., Meyerov, I. (eds) Mathematical Modeling and Supercomputer Technologies. MMST 2022. Communications in Computer and Information Science, vol 1750. Springer, Cham. https://doi.org/10.1007/978-3-031-24145-1_4

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  • DOI: https://doi.org/10.1007/978-3-031-24145-1_4

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