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Entropy, издание 23, том 1, номера страниц: 1-26

Towards generative design of computationally efficient mathematical models with evolutionary learning

Тип публикацииJournal Article
Дата публикации2020-12-27
Multidisciplinary Digital Publishing Institute (MDPI)
Multidisciplinary Digital Publishing Institute (MDPI)
ЖурналEntropy
Квартиль SCImagoQ2
Квартиль WOSQ2
Impact factor2.7
ISSN10994300
General Physics and Astronomy
Краткое описание

In this paper, we describe the concept of generative design approach applied to the automated evolutionary learning of mathematical models in a computationally efficient way. To formalize the problems of models’ design and co-design, the generalized formulation of the modeling workflow is proposed. A parallelized evolutionary learning approach for the identification of model structure is described for the equation-based model and composite machine learning models. Moreover, the involvement of the performance models in the design process is analyzed. A set of experiments with various models and computational resources is conducted to verify different aspects of the proposed approach.

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ГОСТ |
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1. Kalyuzhnaya A. V. и др. Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning // Entropy. 2020. Т. 23. № 1. С. 28.
RIS |
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TY - JOUR

DO - 10.3390/e23010028

UR - http://dx.doi.org/10.3390/e23010028

TI - Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning

T2 - Entropy

AU - Kalyuzhnaya, Anna V.

AU - Nikitin, Nikolay O.

AU - Hvatov, Alexander

AU - Maslyaev, Mikhail

AU - Yachmenkov, Mikhail

AU - Boukhanovsky, Alexander

PY - 2020

DA - 2020/12/27

PB - MDPI AG

SP - 28

IS - 1

VL - 23

SN - 1099-4300

ER -

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@article{Kalyuzhnaya_2020,

doi = {10.3390/e23010028},

url = {https://doi.org/10.3390%2Fe23010028},

year = 2020,

month = {dec},

publisher = {{MDPI} {AG}},

volume = {23},

number = {1},

pages = {28},

author = {Anna V. Kalyuzhnaya and Nikolay O. Nikitin and Alexander Hvatov and Mikhail Maslyaev and Mikhail Yachmenkov and Alexander Boukhanovsky},

title = {Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning},

journal = {Entropy}

}

MLA
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Kalyuzhnaya, Anna V., et al. “Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning.” Entropy, vol. 23, no. 1, Dec. 2020, p. 28. Crossref, https://doi.org/10.3390/e23010028.