Theoretical Framework for Determination of Linear Structures in Multidimensional Geodynamic Data ArraysстатьяИсследовательская статья
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 3 февраля 2022 г.
Аннотация:The article addresses the issue of clustering of multidimensional data arrays with a noiseusing the methods of discrete mathematical analysis (DMA clustering). The theory of DMA clusteringthrough the logical densities calculus is detailed, and the new algorithm Linear Discrete PerfectSets (LDPS) is described. The main objective of the LDPS algorithm is to identify linearly stretchedanomalies in a multidimensional array of geo-spatial data (geophysical fields, geochemistry, satelliteimages, local topography, maps of recent crustal movements, seismic monitoring data, etc.). Thesetypes of anomalies are associated with tectonic structures in the upper part of the Earth’s crustand pose the biggest threat for integrity of the isolation properties of the geological environment,including in regions of high-level radioactive waste disposal. The main advantage of the LDPSalgorithm as compared to other cluster analysis algorithms that may be used in arrays with a noise isthat it is more focused on searching for clusters that are linear. The LDPS algorithm can apply notonly in the analysis of spatial natural objects and fields but also to elongated lineament structures.