Artikel
Open Access
Rock Permeability Forecasts Using Machine Learning and Monte Carlo Committee Machines
-
Simon Katz
,
George Chilingar
Veröffentlicht/Copyright:
25. März 2019
Received: 2016-11-17
Accepted: 2016-12-18
Published Online: 2019-03-25
Published in Print: 2016-12-01
© 2016 Simon Katz et al., published by Sciendo
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- The World Needs Nuclear Power
- The Sustainability of Wind Energy Systems: The Composite Blades Loophole
- An Analytical Thermal-Model for Optimization of Gas-Drilling in Unconventional Tight-Sand Reservoirs
- Evaluating Modeling Approaches for Analyzing Macroeconomic Impacts of Microgrid Projects
- Rock Permeability Forecasts Using Machine Learning and Monte Carlo Committee Machines
Schlagwörter für diesen Artikel
Permeability forecast;
linear regression;
machine learning;
Monte Carlo cross validation;
committee machines
Creative Commons
BY-NC-ND 3.0
Artikel in diesem Heft
- The World Needs Nuclear Power
- The Sustainability of Wind Energy Systems: The Composite Blades Loophole
- An Analytical Thermal-Model for Optimization of Gas-Drilling in Unconventional Tight-Sand Reservoirs
- Evaluating Modeling Approaches for Analyzing Macroeconomic Impacts of Microgrid Projects
- Rock Permeability Forecasts Using Machine Learning and Monte Carlo Committee Machines
