English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The article is devoted to the analysis of the time series, obtained from seismic and deformation monitoring from closed works of Kukisvumchorr deposit JSC "Apatite". The objective of this study is to develop a method for assessing the results of monitoring geomechanical processes in the rock mass on the example of the Kirov mine JSC "Apatit". As a result of closed works, rock masses are changing its natural state of stress. This article has consistently outlined the use of machine learning algorithms in applied problems of geomechanics and geoinformatics. By comparing the schedule of mining operations and seismic activity data with time series of deformations, it is possible to obtain a functional relationship that predicts the distribution of deformations in the rock massif. The results of a computational experiment illustrating the possibility and feasibility of using machine learning algorithms in solving geomechanics problems are presented.

Analysis of the time series of seismic and deformation monitoring, obtained from closed works at the Kirovsky mine of JSC "Apatite"