Green Marketing Performance Statistics Based on AHP and BP Neural Network Models

Abstract

In order to promote the development of circular economy, starting from green marketing is the best means. Combining artificial neural network technology and hierarchical analysis subjective evaluation method, the key factors affecting green marketing performance were analyzed by constructing an evaluation index system for green marketing performance statistics, and the relative weights of each performance indicator were calculated by using analytic hierarchy process (AHP) and the relative importance ranking was given. Then the evaluation results were introduced into the neural network model as input variables. The evaluation results are trained and tested by using the inverse inverse propagation neural network. Finally, the simulation results show that the model can not only reduce the defects of subjective randomness, but also improve the predictability, accuracy and effectiveness of green marketing performance statistics. The calculation results are accurate, the method is feasible, and the errors are controllable, which has theoretical scientific significance and practical guiding significance.