Study on Express Parcels Classification Encoding Method based on Deep Convolutional Neural Network

Abstract

With the rapid development of express delivery business, a large number of express parcels require accurate classification by coding to achieve fast sorting and delivery. In response to the differentiated and precise delivery needs of express parcels, this paper studies the method of dividing express parcels priorities using deep neural networks. By establishing a deep neural network model and training, different express parcels priorities are divided using direct information of express parcels. Neural network training and testing data sample simulation generation, with sample data generation strategies designed based on actual logistics and distribution needs. The structure and configuration parameters of the deep neural network were ultimately determined through training and testing. The priority of parcels is obtained through deep neural networks, and the priority is encoded together with direct information of express parcels for fast sorting and delivery, which providing a reference for classification and coding methods for differentiated and precise delivery of express parcels.