Credit system of smart logistics public information platform based on improved neural network

In-depth discussion and research on the credit issues of the logistics industry are not only of vital significance to the in-depth development of the logistics industry, but also have a significant impact on the sustainable development of the entire logistics industry and even the Chinese economy. This paper combines machine learning algorithms to improve the neural network and builds a credit system for the smart logistics public information platform. When studying the credit evaluation index system of logistics enterprises, the majority of logistics consumers are used as the evaluation subject, and the logistics users are surveyed, and the initial index system established is scored. Then, the method of factor analysis is used to sort and analyze the results of the questionnaire and determine the final evaluation index. In addition, according to the development of logistics enterprises themselves, this paper uses the analytic hierarchy process to evaluate the credit ratings of logistics enterprises from the perspectives of logistics enterprise customers and managers. This will be more authentic and convincing for the evaluation results.