• 31 Citations
  • 3 h-Index
20142019
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Fingerprint Dive into the research topics where Александр Геннадьевич Буевич is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 9 Similar Profiles
kriging Physics & Astronomy
self organizing systems Physics & Astronomy
forecasting Physics & Astronomy
artificial neural network Earth & Environmental Sciences
soils Physics & Astronomy
contaminants Physics & Astronomy
chromium Physics & Astronomy
spatial distribution Physics & Astronomy

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Research Output 2014 2019

  • 31 Citations
  • 3 h-Index
  • 21 Conference contribution
  • 10 Article
  • 1 Chapter
  • 1 Conference article

Combining spatial autocorrelation with machine learning increases prediction accuracy of soil heavy metals

Sergeev, A. P., Buevich, A. G., Baglaeva, E. M. & Shichkin, A. V., 1 Mar 2019, In : Catena. 174, p. 425-435 11 p.

Research output: Contribution to journalArticleResearchpeer-review

artificial neural network
autocorrelation
heavy metal
prediction
soil

Particulate matter size distribution in air surface layer of Middle Ural and Arctic territories

Baglaeva, E. M., Sergeev, A. P., Buevich, A. G., Subbotina, I. E. & Shichkin, A. V., 1 Jul 2019, In : Atmospheric Pollution Research. 10, 4, p. 1220-1226 7 p.

Research output: Contribution to journalArticleResearchpeer-review

Particle size analysis
particulate matter
surface layer
particle size
air

Analysis of time series of greenhouse gas concentrations in the Russian Arctic using the artificial neural networks

Shichkin, A., Buevich, A., Sergeev, A., Antonov, K. & Sergeeva, M., 30 Nov 2018, International Conference of Computational Methods in Sciences and Engineering 2018, ICCMSE 2018. Simos, T. E., Kalogiratou, Z., Monovasilis, T., Simos, T. E. & Simos, T. E. (eds.). American Institute of Physics Inc., Vol. 2040. 050009

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

greenhouses
forecasting
gases
self organizing systems
Russian Federation

Chromium distribution forecasting in subarctic noyabrsk using cokriging, generalized regression neural network, multilayer perceptron, and hybrid technique

Buevich, A. G., Sergeev, A. P., Shichkin, A. V., Kosachenko, A. I. & Moskaleva, A. S., 1 Jan 2018, In : CEUR Workshop Proceedings. 2076, p. 39-48 10 p.

Research output: Contribution to journalConference articleResearchpeer-review

Multilayer neural networks
Chromium
Neural networks
Contamination
Learning systems