Evaluation of Logistics Reputation Based on Principal Component Analysis and BP Neural Network

In order to reduce the risk of the buyers' purchase and avoid the problems of future returns and replacement after purchase, we need to sort out the credit of the seller of the electricity supplier to implement different purchase risk control strategies. Based on the principal component analysis and BP neural network, this paper selects the evaluation results of e-commerce buyers, combines with questionnaire surveys and expert analysis to establish a more referential index system so that the credit evaluation model of e-commerce sellers is established. The case study shows that the index system and the mathematical model can accurately judge the seller's credit rating, and have a strong guiding significance for buyers and enterprises to choose partners.