№3 (2024)

DOI:10.47148/1609-364X-2024-3 Theoretical and methodological bases for visualizing geospatial data, linked data and multimedia data without programmingKukharenko E.L..Development of a GIS-module for analog search using an analytical no-code-platformProzorova G.V., Kling E.E. Application of machine learning classification algorithms to predict probability of channel … Continue reading

Application of the permutation method to the assessment of predictive ability of the models of spatial distribution of copper and iron concentrations in the topsoil

№2 (2022) Sergeev A.P., Butorova A.S., Shichkin A.V., Buevich A.G., Baglaeva E.M., Subbotina I.E. УДК 504.064.2.001.18 https://doi.org/10.47148/1609-364X-2022-2-42-53 Key words: permutation method, randomization, predicted values, observed values, spatial distribution, predictive ability assessment, artificial neural networks Section: Modeling geo objects and geo-processes