The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study interconnections among these determinants. Technically, the research was performed by R programming language, statistical analysis, and QuantumGIS. Methodology includes a range of the statistical methods for data processing, the most important of which is cluster analysis. The results revealed unevenness of the factors affecting trench bathymetric structure, caused by the environmental conditions.

Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean / Polina Lemenkova. - ELETTRONICO. - (2018), pp. 147-152. (Intervento presentato al convegno Virtual Simulation, Prototyping and Industrial Design tenutosi a Tambov, Russia nel 14-16 November 2018) [10.6084/m9.figshare.7531550].

Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean

Polina Lemenkova
Primo
2018

Abstract

The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study interconnections among these determinants. Technically, the research was performed by R programming language, statistical analysis, and QuantumGIS. Methodology includes a range of the statistical methods for data processing, the most important of which is cluster analysis. The results revealed unevenness of the factors affecting trench bathymetric structure, caused by the environmental conditions.
2018
Proceedings of the 5th International Conference
147
152
Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean / Polina Lemenkova. - ELETTRONICO. - (2018), pp. 147-152. (Intervento presentato al convegno Virtual Simulation, Prototyping and Industrial Design tenutosi a Tambov, Russia nel 14-16 November 2018) [10.6084/m9.figshare.7531550].
Polina Lemenkova
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/968191
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