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

Результат исследований: Вклад в журналСтатьяНаучно-исследовательскаярецензирование

14 Цитирования (Scopus)
Язык оригиналаАнглийский
Страницы (с-по)188-197
Число страниц10
ЖурналApplied Geochemistry
Том88
DOI
СостояниеОпубликовано - 1 янв 2018

Отпечаток

kriging
artificial neural network
topsoil
Multilayer neural networks
Pollution
Neural networks
pollution
Mean square error
Chromium
chromium
Chemical elements
environmental modeling
chemical element
Contamination
prediction
computer simulation
Computer simulation
anomaly

Ключевые слова

    Предметные области ASJC Scopus

    • Environmental Chemistry
    • Pollution
    • Geochemistry and Petrology

    Предметные области WoS

    • Геохимия и геофизика

    Цитировать

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    title = "High variation topsoil pollution forecasting in the Russian Subarctic: Using artificial neural networks combined with residual kriging",
    keywords = "Artificial neural networks, Chromium, Combined modeling, GRNNRK, MLPRK",
    author = "Tarasov, {D. A.} and Buevich, {A. G.} and Sergeev, {A. P.} and Shichkin, {A. V.}",
    year = "2018",
    month = "1",
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    doi = "10.1016/j.apgeochem.2017.07.007",
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    journal = "Applied Geochemistry",
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    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.

    В: Applied Geochemistry, Том 88, 01.01.2018, стр. 188-197.

    Результат исследований: Вклад в журналСтатьяНаучно-исследовательскаярецензирование

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    AU - Buevich, A. G.

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    AU - Shichkin, A. V.

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    KW - Combined modeling

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    JF - Applied Geochemistry

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