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  1. Article › Research › Not peer-reviewed

  2. ОЦЕНКА ЗАГРЯЗНЕНИЯ ТЯЖЕЛЫМИ МЕТАЛЛАМИ ГОРОДСКОЙ СРЕДЫ НА ОСНОВЕ ИССЛЕДОВАНИЯ СОВРЕМЕННЫХ АНТРОПОГЕННЫХ ОТЛОЖЕНИЙ

    Селезнев, А. А., Ярмошенко, И. В., Сергеев, А. П., Савастьянова, А. С. & Рахматова, А. Ю., 2016, In: Экологические системы и приборы. 10, p. 39-47 9 p.

    Research output: Contribution to journal › Article

  3. ПРИМЕНЕНИЕ ГЕОСТАТИСТИЧЕСКОГО И НЕЙРОСЕТЕВОГО ПОДХОДА ДЛЯ ОЦЕНКИ ПОВЕРХНОСТНОГО РАСПРЕДЕЛЕНИЯ ПРИМЕСЕЙ В СНЕГОВОМ ПОКРОВЕ НА ТЕРРИТОРИИ МИКРОРАЙОНА АКАДЕМИЧЕСКИЙ ГОРОДА ЕКАТЕРИНБУРГА

    Буевич, А. Г., Сергеев, А. П., Шичкин, А. В., Медведева, М. А. & Баглаева, Е. М., 2016, In: Экологические системы и приборы. 10, p. 3-17 15 p.

    Research output: Contribution to journal › Article

  4. Article › Research › Peer-reviewed

  5. 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

  6. 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

  7. Anamnestic, clinical and laboratory features of the acute period of ischemic stroke in young patients

    Gusev, V. V., Kovtun, O. P., Lvova, O. A., Partylova, E. A., Sergeev, A. P., Sergeeva, M. V., Yanchuk, I. T., Dobrazova, D. A., Suvorkov, P. A. & Shamalov, N. A., 2022, In: Nevrologiya, Neiropsikhiatriya, Psikhosomatika. 14, 3, p. 12-18 7 p.

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

  8. 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

  9. Counter-prediction approach to predict the missing values of a spatial series on the example of the dustiness in the snow cover

    Sergeev, A. P., Shichkin, A. V., Buevich, A. G. & Baglaeva, E. M., 1 Jun 2023, In: Modeling Earth Systems and Environment. 9, 2, p. 1523-1530 8 p.

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

  10. Forecasting of some greenhouse gases content trend in the air of the Russian Arctic region

    Baglaeva, E., Buevich, A., Sergeev, A., Rakhmatova, A. & Shichkin, A., Feb 2021, In: Atmospheric Pollution Research. 12, 2, p. 68-75 8 p.

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

  11. Generalization of the classical signal detection theory for the less-equal-more task

    Sergeev, A., Rakhmatova, A., Buevich, A., Symanyuk, E. & Pavlova, S., 15 Sept 2020, In: Mathematical Methods in the Applied Sciences. 43, 13, p. 7834-7840 7 p.

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

  12. High variation topsoil pollution forecasting in the Russian Subarctic: Using artificial neural networks combined with residual kriging

    Tarasov, D. A., Buevich, A. G., Sergeev, A. P. & Shichkin, A. V., 1 Jan 2018, In: Applied Geochemistry. 88, p. 188-197 10 p.

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

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