Study on Screening Parameter Optimization of Wet Sand and Gravel Particles Using the GWO-SVR Algorithm

The optimization of screening parameters will directly improve the performance vibration screens, which has been a concern industry. In this work, discrete element model wet sand and gravel particles is established, process simulated using method (DEM). efficiency time are used as evaluation indices, including amplitude, frequency, direction angle, screen surface inclination, long short half-axis ratio track, feeding rate, length investigated. results an orthogonal experiment range analysis show that frequency significant factors affecting performance. Then, support vector regression optimized with grey wolf optimizer (GWO-SVR) algorithm to data. excellent learning prediction ability obtained Gaussian kernel function setting. Moreover, GWO-SVR optimize parameters, optimal obtained. Furthermore, effectiveness reliability verified calculation. strategy proposed in work could provide guidance for structural design screens optimization.