scholarly journals Regionalization of geographical space according to selected topographic factors in reference to spatial distribution of precipitation: application of artificial neural networks in GIS

2018 ◽  
Vol 77 (18) ◽  
Author(s):  
Joanna Bac-Bronowicz ◽  
Piotr Grzempowski
Keyword(s):  
Neural Networks ◽  
Spatial Distribution ◽  
Artificial Neural Networks ◽  
Topographic Factors ◽  
Artificial Neural ◽  
Geographical Space

scholarly journals LITHOLOGICAL INTERPRETATION ACCORDING TO WELL-LOGGING DATA FOR THE BAZHENOV FORMATION WITH USAGE OF ARTIFICIAL NEURAL NETWORKS

2021 ◽  
Vol 2 (3) ◽  
pp. 3-9
Author(s):  
Elena U. Temnikova ◽  
Serafim I. Grubas ◽  
Arsenii A. Fedoseev
Keyword(s):  
Neural Networks ◽  
Spatial Distribution ◽  
Artificial Neural Networks ◽  
Well Logging ◽  
Data Models ◽  
Relative Content ◽  
Material Composition ◽  
Bazhenov Formation ◽  
Modern Classification ◽  
Artificial Neural

Using artificial neural networks for lithological interpretation according to well logging data, models of the relative content of rock-forming components of the Bazhenov Formation were constructed and its main types of rocks were identified in accordance with a modern classification. Results of lithological interpretation were used for building correlation schemes, which made it possible to trace the spatial distribution of the material composition and main types of rocks of the Bazhenov Formation for the Salym field.

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural
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