In this study, experimental wear losses under different loads and sliding distances of AISI 1020 steel surfaces coated with (wt.%) 50FeCrC-20FeW-30FeB and 70FeCrC-30FeB powder mixtures by plasma transfer arc welding were determined. The dataset comprised 99 different wear amount measurements obtained experimentally in the laboratory. The linear regression (LR), support vector machine (SVM), and Gaussian process regression (GPR) algorithms are used for predicting wear quantities. A success rate of 0.93 was obtained from the LR algorithm and 0.96 from the SVM and GPR algorithms.

中文翻译：

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使用不同的机器学习算法预测铁合金涂层的磨损量

在这项研究中，确定了通过等离子转移弧焊涂覆（重量％）50FeCrC-20FeW-30FeB和70FeCrC-30FeB粉末混合物的AISI 1020钢表面在不同载荷和滑动距离下的实验磨损损失。该数据集包含在实验室中通过实验获得的99种不同的磨损量测量值。线性回归（LR），支持向量机（SVM）和高斯过程回归（GPR）算法用于预测磨损量。从LR算法获得的成功率为0.93，从SVM和GPR算法获得的成功率为0.96。