基于主成分分析和人工神经网络的酒类辨识

介绍了人工嗅觉系统对不同酒类样本的定性识别,尝试利用主成分分析(PCA)和人工神经网络(ANN)中改进的BP算法、改进的RBF算法(最近邻RBF与k均值RBF相结合选取中心的算法)和k均值RBF算法,实现对酒类的定性识别.实验结果表明:结合PCA的ANN方式为模式识别、分类提供了快速准确的辨识方法.

The identification of wine based on PCA and ANN

The qualitative identification of different wine through artificial electronic nose are introduced.PCA and ANN(including improved BP algorithm and RBF algorithm combining nearest neighbor-clustering algorithm and K-means clustering algorithm) are adopted to realize the identification.The test result indicated that the rapid and exact identification measure of ANN combining PCA is provided to the pattern identification.