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Showing 1 to 3 of 3 for “"Support vector machine regression"”.

  1. Global solution to parametric complementarity constrained programs and applications in optimal parameter selection

    … of bi-parametric LPCC is the Cross-validated Support Vector Machine Regression Parameters Selection Problem. The Support vector machine regression is a robust regression method to minimize the sum of deducted residuals, and thus is less sensitive to changes of data points near the regression

    uiuc Repository record for Global solution to parametric complementarity constrained programs and applications in optimal parameter selection (opens in a new tab)

  2. Analysis and management of low flows in small catchments of Brandenburg, Germany

    … the low flow period was prolonged. A non-linear support vector machine regression was applied to iteratively select meteorological predictors for annual 30-day minimum runoff in 16 catchments between 1965 and 2006. The potential evapotranspiration sum of the previous 48 months was the most …

    potsdam-diss Repository record for Analysis and management of low flows in small catchments of Brandenburg, Germany (opens in a new tab)

  3. Application of Machine Learning and Deep Learning Methods in Geological Carbon Sequestration Across Multiple Spatial Scales

    … capability, and the developments of machine learning (ML) and deep learning (DL) algorithms provide novel perspectives for expanding the knowledge from data, which can capture highly complex nonlinear relationships between multivariate inputs and outputs. This work applied ML and DL …

    vt Repository record for Application of Machine Learning and Deep Learning Methods in Geological Carbon Sequestration Across Multiple Spatial Scales (opens in a new tab)