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

  1. Comparison of linearization methods for modeling the Langmuir adsorption isotherm

    Xuan Guo, Jianlong Wang

    Мақола20195 иқтибос
    ABI
  2. FSRF:An Improved Random Forest for Classification

    Wenxian Feng, Chenkai Ma, Guozhang Zhao +1

    Мақола20204 иқтибос
    ABI
  3. Elastic Net Nonparallel Hyperplane Support Vector Machine and Its Geometrical Rationality

    Kai Qi, Hu Yang

    Мақола20214 иқтибос
    ABI
  4. Linear regression

    Thomas M.H. Hope

    Боб20194 иқтибос
    ABI
  5. Current State of Application of Machine Learning for Investigation of MgO-C Refractories: A Review

    Sebastian Sado, Ilona Jastrzębska, W Zelik +1

    Шарҳ мақола20234 иқтибос
    ABI
  6. A comparative analysis on linear regression and support vector regression

    S. Kavitha, S. Varuna, R. Ramya

    Мақола20163 иқтибос
    ABI
  7. K-Nearest Neighbors

    Oliver Krämer

    Боб20133 иқтибос
    ABI
  8. The Generalized LASSO

    Volker Röth

    Мақола20043 иқтибос
    ABI
  9. Ridge Regression: A Historical Context

    Roger W. Hoerl

    Мақола20203 иқтибос
    ABI
  10. Treatment and Prevention of Stuck Pipe Based on Artificial Neural Networks Analysis

    Qi Zhu

    Мақола20223 иқтибос
    ABI
  11. Prediction of heating and cooling loads based on light gradient boosting machine algorithms

    Jiaxin Guo, Sining Yun, Yao Meng +5

    Мақола20233 иқтибос
    ABI