On the regression of velocity distribution of debris flows using machine learning techniques

Li-Jeng Huang & Darn-Horng Hsiao
Five machine learning techniques-- classical nonlinear regression (NLR), multi-layer perceptrons (MLP), support vector machines (SVM) with radial-basis function (RBF) kernel, k nearest neighbour (kNN) and decision tree (DT) schemes-- were applied for regression of velocity distribution along the depth of debris flows by using experimental data of steady uniform open-channel flows. Programs coded in Python and package scikit-learn were developed for machine learning analyses. Experimental results of two cases conducted and published by Matsumura and...
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