Support Vector Machine: Principles, Parameters, and Applications
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Elsevier
Reference39 articles.
1. Proposing drilling locations based on the 3D modeling results of fluid inclusion data using the support vector regression method;Abbaszadeh;J. Geochem. Explor.,2016
2. Support Vector Machines for Pattern Classification;Abe,2008
3. Interfacial tension between CO2 and brine (NaCl+CaCl2) at elevated pressures and temperatures: the additive effects of different salts;Aggelopoulos;Adv. Water Recourse,2011
4. Development of robust model to estimate gas–oil interfacial tension using least square support vector machine: experimental and modeling study;Ahmadi;J. Supercrit. Fluids,2016
5. Support vector regression for porosity prediction in a heterogeneous reservoir: a comparative study;Al-Anazi;Comput. Geosci.,2010
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