关键词: 白酒识别, 电子鼻, 小波神经网络, 遗传算法

Abstract: The classification model of BP neural networks is put forward, which using electronic nose to acquire odor datum from four kinds of Chinese Liquors, aims at the research of Chinese liquors identification electronic nose. But the BP algorithm of neural network commonly used has several disadvantages, such as the slow convergence speed, the optimization procedure getting easily stacked into the minimal value locally and network parameter must be decided by experiment and experience. This paper designs a recognition classifier of Genetic Algorithm-Wavelet Neural Network（GA-WNN）, which has global optimization capability of GA, non-linear approximation ability of wavelet and self-learning characteristic of neural network. The simulation results prove that it can improve the recognition accuracy and convergence rate, and the GA-WNN algorithm can be used in Chinese liquors identification electronic nose.

Key words: Chinese liquors identification, electronic nose, wavelet neural networks, genetic algorithm