Temperature Prediction of Roughing Inlet Slab based on Machine Learning
WANG Bin
Abstract：In order to improve the quality and performance of hot continuous rolling products,the modeling and prediction of roughing inlet temperature were studied.A prediction model of roughing inlet slab temperature based on machine learning was established.Firstly,the temperature of roughing inlet slab collected by sensor was preprocessed.Secondly,the intelligent particle swarm optimization(PSO)algorithm was used to optimize the least squares support vector machine(LSSVM)prediction model.Finally,a PSO-LSSVM inlet slab temperature prediction model was established.Through a large number of data training and optimization simulation,the results show that the model has high prediction accuracy and good fitting effect.
Keywords：temperature forecastingparticle swarm optimizationprediction modeldata
Publication Date：2024-06-20
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：2( 54-55 )