Counter-prediction method of the spatial series on the example of the dust content in the snow cover

№1 (2022) УДК 504.064.2.001.18https://doi.org/10.47148/1609-364X-2022-1-32-39 Butorova A.S., Sergeev A.P., Shichkin A.V., Buevich A.G., Baglaeva E.M.,Sergeeva M.V. Keywords: counter-prediction method, missing data recovering, artificial neural networks, snow cover, dust. Section: Modeling geo objects and geo-processes

Prediction of prospective areas for gold-cupper-porphyry type of mineralization based on analysis of informative feature search and their functional and correlation relationships.

№2 (2016) Ivanova J.N., Bochneva A.A. Section: Modeling geo objects and geo-processes Keywords: gold-cupper-porphyry type of mineralization, expert assessments, risk zones, bifurcation diagram, predictive function, the Polar Urals.

Operative regional prediction activity of landslide process on the example of Sochi polygon.

№4 (2018) Vozhik A.A.,Shamurzaeva D.A. Section: Geoecology Keywords: Sochi polygon, landslide process, prediction, meteorological factors of activation, landslide hazard.

Optimization of the initial data division for prediction chromium spatial distribution by a feedforward neural network.

№4 (2019) Buevich A.G.,Sergeev A.P.,Rakhmatova A.Yu., Baglaeva E.M.,Shichkin A.V., Subbotina I.E.,Sergeeva M.V.,Markelov Yu.I. Section: Modeling geo objects and geo-processes Keywords: artificial neural networks, multilayer perceptron, modeling, sampling.

Method for constructing a digital twin of a coalrock mass for modeling the integrated development of the Kuzbass subsurface

№1 (2025) Stepanov Y.A., Burmin L.N. УДК 004.942; 004.62 https://doi.org/10.47148/1609-364X-2025-1-57-65 Key words: geoinformatics; GIS; coal-rock mass; digital twin; modeling; geological structure; integrated development; Kuzbass. Section: Information systems in geology and geophysics

Episodes of high correlation of the annual numbers of earthquakes and the slops of the earthquake recurrence graphs of the Baikal Region

№1 (2025) Kakourova A.A., Dem’yanovich V.M., Klyuchevskaya A.A., Dzhurik V.I., Bryzhak E.V. УДК 550.34.042(4+43) https://doi.org/10.47148/1609-364X-2025-1-22-34 Key words: Baikal rift system; earthquakes; slope of earthquake recurrence graph; seismicity, seismic process; number of earthquakes. Section: Modeling geo objects and geo-processes

Review and Analysis of XAI Methods for Addressing Geoecological Zoning and Public Health Prevention Challenges

№4 (2024) Trofimov Yu.V., Averkin A.N., Cheremisina E.N. УДК 0048 https://doi.org/10.47148/1609-364X-2024-4-93-118 Key words: sustainable development; explainable artificial intelligence (XAI); ecological zoning; geographic information systems (GIS); neuro-fuzzy models; disease prevention; environmental risks; decision support systems; healthcare Section: Artifical intelligence in applied … Continue reading →

Basic artificial Intelligence tasks in сontext of geological prospecting

№4 (2024) Сheremisina E.N., Kirpicheva E.Y., Tokareva N.A., Milovidova A.A. УДК 004.8, 303.732, 550.8.01https://doi.org/10.47148/1609-364X-2024-4-83-92 Key words: artificial Intelligence; multidisciplinary research; explainable artificial intelligence; machine learning; neural networks; systematic approach Section: Artifical intelligence in applied fields of knowledge

Development of an information and calculation complex for assessing the radioecological situation on radioactively contaminated agricultural land

№4 (2024) Krechetnikov V.V., Titov I.E., Krechetnikova E.O., Kuznetsov V.K. УДК 528.952:631.95 https://doi.org/10.47148/1609-364X-2024-4-21-28 Key words: radioactive contamination, agrolandscapes, radionuclides, accumulation of radionuclides, attribute data base, GIS, information and calculation complex, calculation and analytical modules. Section: Application of GIS technologies

Development of a methodology for empirical scientific research using standard libraries of automatic machine learning on the example of predicting oil and gas reservoirs in the Tomsk Region

№1 (2024) Vladimir A. Ostanin УДК 004.89, 550.8.05, 167.7 https://doi.org/10.47148/1609-364X-2024-1-4-18 Key words: interpretation of geophysical data, design of geological exploration works for oil and gas, design of oil and gas field development, automatic machine learning, AutoML, AI, autokeras, SHAP, LIME … Continue reading →

Geoinformatika

Journal of geoinformation technologies in geology and geoecology

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