A tea variety classification method for fuzzy inter-cluster separation and clustering

Abstract

The invention discloses a tea variety classification method based on fuzzy inter-cluster separation and clustering. The method comprises the following steps: S1, carrying out Fourier near infrared spectrum collection on a tea sample; S2, carrying out pretreatment on the near infrared spectrum of the tea leaf sample by using multivariate scattering correction; S3, realizing near infrared spectrum dimension reduction treatment by using principal component analysis; S4, realizing identification information extraction of the near infrared spectrum data by using linear discriminant analysis; And S5, carrying out tea variety classification by using fuzzy inter-cluster separation clustering. According to the method, the problem that the clustering effect is not ideal when a complex data structureis processed by using traditional fuzzy inter-cluster separation and clustering is solved. The method has the advantages of high detection speed, nondestructive detection, capability of processing complex spectral data, high tea variety classification accuracy and the like.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, in particular to a method for classifying tea varieties based on fuzzy inter-cluster separation and clustering. Background technique [0002] Tea contains tea polyphenols, plant alkaloids, proteins, amino acids, vitamins and other ingredients. Tea has the effects of calming the nerves, improving eyesight, quenching thirst and promoting body fluid, clearing away heat and relieving summer heat. Tea is one of the three major beverages in the world. Drinking tea is a traditional food culture, and offering tea to guests is an etiquette in people's daily social life. However, there are many varieties of tea leaves, and ordinary people cannot distinguish the quality and quality of tea leaves. Therefore, identification of tea varieties is a very important research direction, and it is very necessary and valuable to design a simple and fast method for identification of tea varieties. ...

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the shortcomings existing in the existing class separation and clustering methods in the clustering of tea near-infrared spectrum data, and proposes a tea variety classification method for fuzzy inter-cluster separation and clustering. Compared with the existing class separation and clustering Class method, a tea variety classification method based on fuzzy inter-cluster separation and clustering of the present invention uses an adaptive distance measure based on fuzzy covariance matrix to replace the Euclidean distance measure in the inter-class separation and clustering method

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