智能系统学报Issue(2)：177-182,6.DOI:10.3969/j.issn.1673-4785.201209026
自适应概率神经网络及其在白酒电子鼻中的应用
Application of adaptive probabilistic neural network in Chinese liquor E-Nose
摘要
Abstract
In order to explore the possibility of hard liquor quality recognition by an electronic nose , the Chinese liquor of Yanghe Haizhilan, Jinshiyuan Shengjiedai , Anhui Yingjiadaqu, and Niulanshan Chenniang were analyzed by using self-made new wireless electronic nose for recognition of hard liquor quality .Firstly, the steady-state re-sponse and slope values were extracted after smoothing the collected data .Secondly, principal component analysis PCA was used to reduce the dimension of the eigenvector , and the obtained first two principal components scores were then used as the input parameters of the probabilistic neural network recognition model .Next, the aim was to overcome defect of traditional probabilistic neural network smoothing factor which would cause classification error easily.The method of adaptive probabilistic neural network identification model was presented , utilizing differential evolution algorithm to optimize the set of parameters .The results show that differential evolution -probabilistic neural network obtained a high recognition accuracy and noise immunity compared to back propagation , particle swarm op-timization-probabilistic neural network and support vector machine .The experiment also proved that the electronic nose can effectively detect different liquor brands in China .关键词
差异演化算法/自适应概率神经网络/电子鼻/白酒识别Key words
differential evolution algorithm/adaptive probabilistic neural network/electronic nose/hard liquor quality recognition分类
信息技术与安全科学引用本文复制引用
周红标,张宇林,丁友威,刘佳佳..自适应概率神经网络及其在白酒电子鼻中的应用[J].智能系统学报,2013,(2):177-182,6.基金项目
国家自然科学基金资助项目（61203056）；淮安市科技公共服务平台资助项目（HAP201107）． （）
