Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Alexander V. Boukhanovsky"'
Autor:
Yu.I. Nechaev, S.V. Kovalchuk, Alexander V. Boukhanovsky, Optics, St. Petersburg, Russia, S.V. Ivanov
Publikováno v:
Ontology of Designing. 10:22-33
The conceptual solutions of building an ontological knowledge system in the functional spaces of the modern theory of disasters are discussed. The theoretical basis for the implementation of an ontological knowledge system based on a multifunctional
Autor:
Vladimir V. Voevodin, Angelos Bilas, Alexandra Klimova, Vangelis Harmandaris, Alexander V. Boukhanovsky
Publikováno v:
Procedia Computer Science. 178:1-7
This volume presents selected papers of young scientists – participants of International Young Scientists Conference in Computational Science (YSC’2020). This annual event has been annually organized by ITMO University since 2012 and aims to deve
Publikováno v:
Developments in Maritime Technology and Engineering ISBN: 9781003216599
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::649a5601bc6b4be9ad2372def9ebcd04
https://doi.org/10.1201/9781003216599-82
https://doi.org/10.1201/9781003216599-82
Publikováno v:
Procedia Computer Science. 156:347-356
The problem of the weather forecasting still exists in urban agglomerations, in part because of local factors on a city scale. It is important to take into acount urban processes, to make a high-resolution weather forecast. In this study, we suggest
Autor:
Pavel Vychuzhanin, Alexander V. Boukhanovsky, Anna V. Kalyuzhnaya, Iana S. Polonskaia, Ilia Revin, Gleb Maximov, Nikolay O. Nikitin, Mikhail Sarafanov, Irina V. Barabanova
The effectiveness of the machine learning methods for real-world tasks depends on the proper structure of the modeling pipeline. The proposed approach is aimed to automate the design of composite machine learning pipelines, which is equivalent to com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53f1382bdc4d736b63a1ae7ced640229
Autor:
Mikhail Maslyaev, Alexander Hvatov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Alexander V. Boukhanovsky, Mikhail Yachmenkov
Publikováno v:
Entropy
Entropy, Vol 23, Iss 28, p 28 (2021)
Volume 23
Issue 1
Entropy, Vol 23, Iss 28, p 28 (2021)
Volume 23
Issue 1
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&rsquo
design and co-design, the ge
design and co-design, the ge
Publikováno v:
GOODTECHS
Often, confidentiality problems and a lack of original data, make it challenging to analyze user data carefully. In such situations, synthetic data can be used that is more suitable for testing and training marketing strategies, personalized assistan
Autor:
Michael Lees, Oksana Severiukhina, Sergey Kesarev, Alexander V. Boukhanovsky, Klavdiya Bochenina, Peter M. A. Sloot
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-17 (2020)
Journal of Big Data, 7:72. Springer Open
Journal of Big Data, 7:72. Springer Open
This research proposes a system based on a combination of various components for parallel modelling and forecasting the processes in networks with data assimilation from the real network. The main novelty of this work consists of the assimilation of
Autor:
Pavel Vychuzhanin, Anna V. Kalyuzhnaya, Alexander Hvatov, Alexander V. Boukhanovsky, Nikolay O. Nikitin
Publikováno v:
GECCO Companion
This paper provides the main concepts of the knowledge-enriched AutoML approach and shortly describes the current results of the proof of concept implementation within the FEDOT framework. By knowledge enrichment, we mean the insertion of domain-spec
Publikováno v:
Complexity, Vol 2020 (2020)
In this paper, we present an approach to drug addiction simulation and forecasting in the medium and long terms in cities having a high population density and a high rate of social communication. Drug addiction forecasting is one of the basic compone