Since there are many factors affecting the quality of wine, total 17 factors were screened out using principle component analysis. The difference test was conducted on the evaluation data of the two groups of testers. The results showed that the evaluation data of the second group were more reliable compared with those of the first group. At the same time, the KM algorithm was optimized using the QPSO algorithm. The wine classification model was established. Compared with the other two algorithms, the QPSO-KM algorithm was more capable of searching the globally optimum solution, and it could be used to classify the wine samples. In addition,the QPSO-KM algorithm could also be used to solve the issues about clustering.
