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  1. A hybrid method for assessment of soil pollutants spatial distribution

    Tarasov, D. A., Medvedev, A. N., Sergeev, A. P., Shichkin, A. V. & Buevich, A. G., 21 Jul 2017, International Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2016. American Institute of Physics Inc., Vol. 1863. 050015

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  2. A permutation approach to evaluating the performance of a forecasting model of methane content in the atmospheric surface layer of arctic region

    Sergeev, A., Shichkin, A., Baglaeva, E., Buevich, A. & Butorova, A., 1 Feb 2024, In: Atmospheric Pollution Research. 15, 2, 102000.

    Research output: Contribution to journal › Article › peer-review

  3. A two-step combined algorithm based on NARX neural network and the subsequent prediction of the residues improves prediction accuracy of the greenhouse gases concentrations

    Buevich, A., Sergeev, A., Shichkin, A. & Baglaeva, E., Mar 2021, In: Neural Computing and Applications. 33, 5, p. 1547-1557 11 p.

    Research output: Contribution to journal › Article › peer-review

  4. About data separation for the artificial neural network training to predict the spatial distribution of the chemical element in the soil

    Rakhmatova, A. Y., Sergeev, A. P., Shichkin, A. V. & Buevich, A. G., 6 Dec 2019, Physics, Technologies and Innovation, PTI 2019: Proceedings of the VI International Young Researchers Conference. Volkovich, V. A., Zvonarev, S. V., Kashin, I. V., Smirnov, A. A. & Narkhov, E. D. (eds.). American Institute of Physics Inc., 5 p. 020159. (AIP Conference Proceedings; vol. 2174).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  5. 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 proceeding › Conference contribution › peer-review

  6. Application of the Wavelet Data Transformation for the Time Series Forecasting by the Artificial Neural Network: book chapter

    Butorova, A., Baglaeva, E., Subbotina, I., Sergeeva, M., Sergeev, A., Shichkin, A., Buevich, A. & Petrov, P., 18 Mar 2023, New Trends in the Applications of Differential Equations in Sciences: book. Slavova, A. (ed.). Springer Cham, p. 365-370 6 p. (Springer Proceedings in Mathematics & Statistics; vol. 412).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  7. 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 journal › Conference article › peer-review

  8. Chromium distribution forecasting using multilayer perceptron neural network and multilayer perceptron residual kriging

    Tarasov, D., Buevich, A., Shichkin, A., Subbotina, I., Tyagunov, A. & Baglaeva, E., 10 Jul 2018, International Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017. American Institute of Physics Inc., Vol. 1978. 440019

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  9. 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 journal › Article › peer-review

  10. Comparing the Types of Artificial Neural Networks to Predict the Carbon Dioxide Concentration Changes

    Sergeev, A., Buevich, A., Shichkin, A., Baglaeva, E., Subbotina, I. & Sergeeva, M., 6 Apr 2022, International Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2020. Simos, T. E., Simos, T. E., Simos, T. E., Simos, T. E. & Tsitouras, C. (eds.). American Institute of Physics Inc., 110007. (AIP Conference Proceedings; vol. 2425).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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