基于PSO训练SVM的人脸识别 利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径-PSO-based SVM for face recognition training using support vector machine learning ability in the performance of good performance, combined with KPCA

本程序用pca，kpca,svm,pls,fisher，神经网络实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十七-The program use pca, kpca, SVM, PLS, fisher, neural networks realize CSTR process inspection and CSTH fault diagnosis, diagnosis rate is ninety-nine percent, and the fault re

本程序用pca，kpca,svm,pls,fisher，神经网络实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十六-The program use pca, kpca, SVM, PLS, fisher, neural networks realize CSTR process inspection and CSTH fault diagnosis, diagnosis rate is ninety-nine percent, and the fault re