Service quality evaluation of fresh agricultural products cold chain logistics based on principal component and neural network

Abstract

With the rapid development of fresh e-commerce, the cold chain logistics service quality of fresh agricultural products has attracted the attention of businesses and customers. Starting from the connotation of cold chain logistics service quality, the evaluation index system of agricultural products cold chain logistics service quality with 13 influencing factors was established. Considering that too many dimensions of input data and strong correlation among indexes will affect the training of neural network, this paper proposes to build a service quality evaluation model of cold chain logistics of fresh agricultural products by combining principal component analysis with BP neural network. Through the actual data verification of an e-commerce logistics enterprise, the evaluation accuracy rate is significantly improved, which provides an effective method for the service quality evaluation of fresh agricultural products cold chain logistics.