Research On Credit Risk Prediction Of Network Freight Operators Based On Entropy Weight Method BP Neural Network Mode

At present,nearly 90% of the total market share of China’s highway transportation enterprises has been occupied by various small and medium-sized logistics transportation companies and individual transportation enterprises.With the continuous development of highway cargo transportation industry,China’s highway cargo transportation volume is increasing year by year,but the problems are also constantly exposed.The matching mechanism between supply and transportation capacity is not perfect,and the supply information is blocked for a long time,resulting in the low level of highway freight service,and even shirking responsibility Dishonesty such as running with goods,no-load operation and waste of resources.In order to solve this problem,China’s Ministry of transport put forward the concept of network freight operator.The emergence of a large number of network freight operators has produced an aggregation effect,which further improves the organization and transportation management level of the logistics market.With the continuous development of network freight operators,their credit risk problems are exposed.Many network freight operators are faced with the practical problem of how to predict credit risk.Therefore,the effective prediction of the credit risk of network freight operators has become the focus of network freight operators,which has important practical value for their survival and development.Based on the basic theory and development status of network freight operators,this paper makes an in-depth study on the credit risk prediction system and prediction model of network freight operators.This paper consists of five chapters.The first chapter is the introduction,which introduces the background and research significance of the topic,summarizes the literature from three aspects: network freight operators,logistics enterprise credit risk prediction index system and logistics enterprise credit risk prediction methods,and puts forward the research objectives,technical routes,research methods and research innovations.The second chapter is the theoretical basis and development status of network freight operators,expounds the concept,characteristics,operation principle,service subject and service type of network freight operators,and analyzes the necessity and limitations of credit risk prediction of network freight operators.The third chapter is the credit risk prediction index system of network freight operators.It introduces the selection principles of credit risk prediction model indexes of network freight operators from four aspects: the principles of comprehensiveness and operability,high efficiency and resource conservation,the combination of qualitative and quantitative principles and scientific principles.It forms the logical structure of 27 prediction index systems from three dimensions: enterprise financial status,enterprise basic quality and enterprise integrity.The fourth chapter is the credit risk prediction model of network freight operators.After introducing the principle and algorithm flow of entropy weight method and BP neural network model,this paper constructs the entropy weight method BP neural network model,analyzes the example,and puts forward some countermeasures and suggestions to improve the credit rating of network freight operators.The fifth chapter is the conclusion,which summarizes the main research results and deficiencies of the article,hoping to provide some reference for the research on the risk prediction of network freight operators.