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pro vyhledávání: '"Restrepo Lopera, Juan Pablo"'
Autor:
Restrepo Lopera, Juan Pablo
This article presents a novel nonparametric approach to generate synthetic data using copulas, which are functions that explain the dependency structure of the real data. The proposed method addresses several challenges faced by existing synthetic da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2653::37f8368031f389c5f006b1f13a48afe3
http://hdl.handle.net/10784/32480
http://hdl.handle.net/10784/32480
Grinding is a very important industrial operation that draws up to 4% of the global electricity consumption. It is imperative to predict accurately the appropriate retention times necessary for a given size reduction to minimize the wasted energy inv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2653::e2c027bda628b35b545f51d37eb96cb9
http://hdl.handle.net/10784/17079
http://hdl.handle.net/10784/17079