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Работы, цитирующие эту работу

Работ: 10

Работа: A comparative analysis of K-Nearest Neighbor, Genetic, Support Vector Machine, Decision Tree, and Long Short Term Memory algorithms in machine learning

  1. Advancing agriculture with machine learning: a new frontier in weed management

    Mohammad Mehdizadeh, Duraid K. A. Al-Taey, Anahita Omidi +5

    СтатьяSmart Agriculture and AIFrontiers of Agricultural Science and Engineering2024Цитирований: 0
    ABI

  2. Predictive modeling of oil rate for wells under gas lift using machine learning

    Fang Ma, Farag M. A. Altalbawy, Pinank Patel +9

    СтатьяReservoir Engineering and Simulation MethodsScientific Reports2025Цитирований: 0
    ABI

  3. Robust forecasting of packaging chemical migration into water and food

    Chuan'an Wei, Farag M. A. Altalbawy, Dharmesh Sur +8

    СтатьяAdvanced Chemical Sensor TechnologiesInternational Journal of Food Properties2025Цитирований: 0
    ABI

  4. Development of robust machine learning models to estimate hydrochar higher heating value and yield based upon biomass proximate analysis

    Guoliang Hou, Ahmed Alkhayyat, Ahmad Almalkawi +8

    СтатьяThermochemical Biomass Conversion ProcessesBioresources and Bioprocessing2025Цитирований: 0
    ABI

  5. Predicting filter cake thickness in drilling fluids using machine learning techniques

    Minghui OU, Mohammed Al-Bahra, Raman Kumar +10

    СтатьяDrilling and Well EngineeringPhysics and Chemistry of the Earth Parts A/B/C2025Цитирований: 0
    ABI

  6. Machine learning approaches for estimating formation enthalpies in energetic materials

    Jianfeng Li, Farag M. A. Altalbawy, Hardik Doshi +8

    СтатьяMachine Learning in Materials ScienceJournal of Energetic Materials2025Цитирований: 0
    ABI

  7. Developing rigorous machine learning models to accurately estimate pesticide photodegradation by ZnO-based photocatalysts in water

    Farag M. A. Altalbawy, Shoira Formanova, Ahmad Almalkawi +7

    СтатьяWater Quality Monitoring and AnalysisJournal of the Indian Chemical Society2025Цитирований: 0
    ABI

  8. Predicting the Storage Modulus of Chromium‐Crosslinked Polymer Gels Through Advanced Machine Learning Techniques

    Farag M. A. Altalbawy, Raed H. C. Alfilh, Tarak Vora +8

    СтатьяMachine Learning in Materials SciencePolymers for Advanced Technologies2026Цитирований: 0
    ABI

  9. 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
    ABI

  10. 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
    ABI