Работы, цитирующие эту работу

Работ: 6

Работа: Gradient Boosting Machine

1. Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data

   Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya +9

   СтатьяReservoir Engineering and Simulation MethodsScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000937

2. Reliable estimation via hybrid gradient boosting machine for mud loss volume in drilling operations

   Xiaozhi Lu, Farag M. A. Altalbawy, Tarak Vora +9

   СтатьяDrilling and Well EngineeringScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002187

3. Application of hybrid gradient boosting machine to reliably predict rate of penetration

   Jianing Zhang, Farag M. A. Altalbawy, Tarak Vora +10

   СтатьяHigh-Velocity Impact and Material BehaviorPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.008755

4. Insightful frameworks for zeta potential of various clays in different brine compositions

   Junhou Wang, Farag M. A. Altalbawy, Suranjana V. Mayani‎ +9

   СтатьяElectrokinetic Soil Remediation TechniquesPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.010595

5. Estimating solubility of nitrogen in various ionic liquids: application of machine-learning

   Kassem Al Attabi, Farzona Alimova, Anupam Yadav +7

   СтатьяIonic liquids properties and applicationsChemical Papers2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.004224

6. Machine learning frameworks to accurately compute CO2 capture in porous liquids

   Farag M. A. Altalbawy, Soumya V. Menon, Anupam Yadav +7

   СтатьяCarbon Dioxide Capture TechnologiesChemical Papers2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.004589