Работы, цитирующие эту работу

Работ: 5

Работа: Characterizing Subsurface Structures From Hard and Soft Data With Multiple‐Condition Fusion Neural Network

1. Enhanced groundwater vulnerability assessment in urban landscapes: An adaptive AHP-GIS modified DRASTIC approach for Kolkata metropolitan area

   Kazi Hamidul Islam, Reshmi Das, Ismail Mondal +2

   СтатьяGroundwater and Watershed AnalysisEnvironment Development and Sustainability2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.other.344436

2. Evaluating green urban underground spaces using PROMETHEE II for ecological suitability

   Yingbin Song, XU Qing, Mohammad R.K.M. Al-Badkubi +1

   СтатьяUnderground infrastructure and sustainabilityApplied Water Science2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001417

3. Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones

   Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora +10

   СтатьяHydraulic Fracturing and Reservoir AnalysisJournal of Petroleum Exploration and Production Technology2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001802

4. Permeability reduction prediction in low-salinity water flooding of clay-rich sandstones through machine learning

   Yifan Li, Farag M. A. Altalbawy, Hardik Doshi +9

   СтатьяHydraulic Fracturing and Reservoir AnalysisPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.007565

5. New insights into residue formation due to oxidation of crude oil via data-driven methods

   Mohammad Abushuhel, Ibrahim Khersan, Tariq Abdulkader Alrihaim +7

   СтатьяPetroleum Processing and AnalysisGeosystem Engineering2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.017440