… However, the actual vibration signals of rotating machinery … Therefore, a rotating machinery
fault diagnosis approach … ), and a light gradient boosting machine (LightGBM), is proposed in …

… Finally, a new optimized LightGBM model is employed to … , we use Bayesian optimization
to determine the most critical … of the final LightGBM model using Bayesian optimization [42]. …

… severity values under variable machine settings. Based on … optimised Light Gradient
Boosting Machine (MPA-LightGBM) for fault diagnosis and severity analysis of rotating machines …

… using Bayesian hyperparameter optimization on LightGBM and then output the LightGBM …
The final step comes to LightGBM online fault detection. By inputting the optimal LightGBM …

… an efficient optimization method for multi-objective optimization of APMM … LightGBM technique
to the multi-objective optimization of other types of machines, such as rotary PM machines …

… for the development of Hyperparameter optimized LightGBM and Stacking Models. The third
… CNC machine having the spindle motor rated at 22 kW and a maximum rotational speed of …

… , and Bayesian optimization algorithm to optimize the model parameters. … optimization by
three methods are shown in Table 2. It can be seen that Grid search and Bayesian optimization …

… Jin et al proposed an intelligent early fault diagnosis method for rotating machinery
based on the parameter optimisation of the VMD and deep multikernel extreme learning …

… If the installed global capacity of rotating equipment using electric drives is … a LightGBM
algorithm based on GBDT to seek the optimal parameters, which enables the pump equipment …

… regarded as a key part of rotating machinery, so fault diagnosis of … optimal solutions, this
paper introduces a global optimization algorithm–BOA to select parameters for the LightGBM…