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Найдено документов в текущей БД: 2

    Model of Prey-Predator Dynamics with Reflexive Spatial Behaviour of Species Based on Optimal Migration
[Text] / M. Sadovsky, M. Senashova // Bull. Math. Biol. - 2016. - Vol. 78, Is. 4. - P736-753, DOI 10.1007/s11538-016-0159-z. - Cited References:58 . - ISSN 0092-8240. - ISSN 1522-9602
РУБ Biology + Mathematical & Computational Biology

Аннотация: We consider the model of spatially distributed community consisting of two species with "predator-prey" interaction; each of the species occupies two stations. Transfer of individuals between the stations (migration) is not random, and migration stipulates the maximization of net reproduction of each species. The spatial distribution pattern is provided by discrete stations, and the dynamics runs in discrete time. For each time moment, firstly a redistribution of individuals between the stations is carried out to maximize the net reproduction, and then the reproduction takes place, with the upgraded abundances. Besides, three versions of the basic model are implemented where each species implements reflexive behaviour strategy to determine the optimal migration flow. It was found that reflexivity gives an advantage to the species realizing such strategy, for some specific sets of parameters. Nevertheless, the regular scanning of the parameters area shows that non-reflexive behaviour yields an advantage in the great majority of parameters combinations.

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Держатели документа:
Inst Computat Modelling SB RAS, Krasnoyarsk, Russia.

Доп.точки доступа:
Sadovsky, Michael; Senashova, Mariya

    Modification of Nonparametric Probability Density Estimation of Parzen's Type with Implicitly Given form of Kernel Function
/ A. V. Lapko, V. A. Lapko, E. A. Yuronen // 2018 INTERNATIONAL SCIENTIFIC MULTI-CONFERENCE ON INDUSTRIAL ENGINEERING : IEEE, 2018. - International Scientific Multi-Conference on Industrial Engineering and (OCT 02-04, 2018, Vladivostok, RUSSIA). - Cited References:31 . - ISBN 978-1-5386-9535-7
РУБ Engineering, Industrial

Аннотация: The new nonparametric probability density estimation based on use of the smoothing operator is offered and investigated. It has smaller dispersion in comparison with probability density estimation like Rosenblatt-Parzen.

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Держатели документа:
Reshetnev Siberian State Univ Sci & Technol, Inst Comp Modelling SB RAS, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Siberian Fed Univ, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, Aleksandr V.; Lapko, Vasiliy A.; Yuronen, Ekaterina A.