Three different machine learning algorithms are applied in this work, including feedforward neural networks (FNN), eXtreme gradient boosting (XGB) and hybrid FNN-XGB. Artificial neural network has been widely used in the field of nonlinear fitting. A simple type of acritical neural work is FNN, which are trained by error backpropagation. The information in FNN moves in only one direction, forward, from the input nodes to the output nodes. XGB is a tree-based ensemble machine learning algorithm, which provides some advantages over the FNN, such as high tolerance, high efficiency and fast calculation speed.