基于核主成分分析与SVM的岩爆烈度组合预测模型

许瑞,侯奎奎,王玺,刘兴全,李夕兵

Combined Prediction Model of Rockburst Intensity Based on Kernel Principal Component Analysis and SVM

Rui XU,Kuikui HOU,Xi WANG,Xingquan LIU,Xibing LI

表5 模型参数及模型训练集和测试集准确率

Table 5 Results for the SVM parameters，training set accuracy and test set accuracy

模型 SVM参数 训练集准确率/% 测试集准确率/% C g PCA GA-SVM 81.4710 56.6212 96.8 84.6 PSO-SVM 97.6345 118.4431 98.2 84.6 KPCA1 GA-SVM 50.5654 890.2415 94.6 73.1 PSO-SVM 51.3095 586.1588 89.6 76.9 KPCA2 GA-SVM 3.1284 256.1905 91.4 88.5 PSO-SVM 31.2537 145.4178 94.6 92.3 KPCA3 GA-SVM 73.1933 282.2821 93.2 80.8 PSO-SVM 82.0614 491.9322 97.7 88.5