Selection of Optimal Packaging Methods for Different Food Based on Big Data Analysis

In order to improve the ability of food packaging optimization and selection, combined with big data analysis method, different food best packaging methods are selected, and a large data classification technology for different food packaging methods based on fuzzy directivity classification is proposed. Big data parametric model which reflects the best packaging characteristics of different foods is extracted, and the extracted packaging parameters are matched by adaptive fuzzy matching. Then, the directional clustering method is used to classify and identify big data, which is combined with the food packaging. The shelf life and food characteristics are processed by big data information fusion to realize the best match between food packaging and food characteristics. The retrieval node graph model grouping method is used to classify different food packaging data to optimize the selection of different food packaging methods. The simulation results show that, the method used to select the best packaging methods for different foods has better intelligence, improving the ability of classification and recognition of food packaging, and promoting the intelligent development of food packaging.