The accurate prediction and analysis of bed expansion characteristics in liquid–solid fluidized bed based on machine learning methods

•Machine learning methods were employed to predict bed expansion ratio.•XGBoost model has good regression and prediction ability with R2 higher than 0.97.•The relative importance of operating variables on bed expansion ratio was obtained.•Particle size has the strongest effect on bed expansion ratio.