【摘要】 以页岩为研究对象,分别采用多元线性回归(MLR)及最小二乘支持向量机(LS-SVM)建立了页岩的单轴抗压强度及抗拉强度预测模型,考虑的间接指标包括:岩石密度、点荷载强度及纵波波速,并对上述两种预测模型进行了性能检验及比较。结果表明:页岩强度与密度、点荷载强度、纵波波速呈较好的线性关系,相关系数均大于0.89;MLR和LS-SVM方法均可得到较高精度的强度值,但单轴抗压强度的预测精度比抗拉强度高,更适合于抗压强度的预测。两类模型在预测岩石单轴抗压强度时效果相当,但LS-SVM方法更适合于抗拉强度的预测。更多还原

【Abstract】 Taking shale as the research object,considering the rock density,point load strength and P-wave velocity,prediction models of uniaxial compressive strength and tensile strength were built by multiple linear regression(MLR)and least squares support vector machine(LS-SVM).And their performances were tested and compared.The results showed that the strength of shale had good linear relations with rock density,point load strength and P-wave velocity,and the correlation coefficients were all greater than 0.89.MLR and LS-SVM could both obtain strength values with high accuracy.But the prediction accuracy of uniaxial compressive strength was higher than that of tensile strength,which proved that MLR and LS-SVM was much more suitable to predict compressive strength.The performances of two methods were equivalent for predicting compressive strength,while LS-SVM method was much more suitable to predict tensile strength.更多还原