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22 ta ish

Ish: Prediction of H <sub>2</sub> S adsorption capacity of biochar using rigorous machine learning frameworks

  1. Machine learning-based estimation of nano-lubricants viscosity in different operating conditions

    Amin Bemani, Mohammad Madani, Alireza Kazemi

    Maqola202326 iqtibos
    ABI

  2. Deterministic tools to predict gas assisted gravity drainage recovery factor

    Maryam Hasanzadeh, Mohammad Madani

    Maqola202312 iqtibos
    ABI

  3. Estimation of adsorption capacity of CO2, CH4, and their binary mixtures in Quidam shale using LSSVM: Application in CO2 enhanced shale gas recovery and CO2 storage

    Amin Bemani, Alireza Baghban, Amir H. Mohammadi +1

    Maqola20206 iqtibos
    ABI

  4. Model averaging prediction by K-fold cross-validation

    Xinyu Zhang, Chu-An Liu

    Maqola20225 iqtibos
    ABI

  5. Prediction of geological characteristics from shield operational parameters by integrating grid search and K-fold cross validation into stacking classification algorithm

    Tao Yan, Shui‐Long Shen, Annan Zhou +1

    Maqola20225 iqtibos
    ABI

  6. Connectionist approaches for solubility prediction of n-alkanes in supercritical carbon dioxide

    Amin Daryasafar, Navid Daryasafar, Mohammad Madani +2

    Maqola20164 iqtibos
    ABI

  7. Optimization and prediction of biogas yield from pretreated Ulva Intestinalis Linnaeus applying statistical-based regression approach and machine learning algorithms

    Uyiosa Osagie Aigbe, Kingsley Eghonghon Ukhurebor, Otolorin Adelaja Osibote +2

    Maqola20244 iqtibos
    ABI

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