Prediction Method of Gas Content Based on GRA-DBO-SVR
To improve the accuracy and efficiency of coal seam methane content prediction,a novel gas content prediction method based on Grey Relational Analysis(GRA),Dung Beetle Optimization(DBO)algorithm,and Support Vector Regression(SVR)model was proposed.First,the GRA is used to screen factors that affect gas content to reduce the dimensionality of the input data for the prediction model.Then,the DBO is employed to optimize the parameters of SVR model,constructing a gas content prediction model based on GRA-DBO-SVR.The prediction results of GRA-DBO-SVR,GRA-PSO-SVR,GRA-SVR,and SVR models are compared.The results show that the Mean Relative Errors(MRE)of GRA-DBO-SVR,GRA-PSO-SVR,GRA-SVR,and SVR are 2.82%,2.98%,3.72%,and 6.02%,respectively;the Mean Absolute Errors(MAE)are 0.28,0.31,0.44,and 0.63,respectively;and the Mean Squared Errors(MSE)are 0.17,0.18,0.37,and 0.90,respectively.The GRA-DBO-SVR model demonstrates better generalization ability,meeting the actual needs of engineering applications.
gas content predictiongrey relational analysisdung beetle optimizationsupport vector regression
万方数据
维普
