Application of Neural Network Sample Training Algorithm in Economic Information Management System

Abstract

In order to make up for the shortcomings of traditional financial evaluation, this paper proposes a method of enterprise comprehensive performance evaluation system based on the balanced scorecard method and BP artificial neural network model. This method focuses on the application methods and steps of BP artificial neural network model in enterprise comprehensive performance evaluation system. In addition, it also makes a detailed study on the initial weight and threshold assignment of the BP network, the selection of training samples, the determination of hidden layer, the convergence of network, and so on. The experimental results show that this method verifies the comprehensive performance evaluation results of 15 manufacturers, and the results are 4 excellent, 5 good, 3 average, 2 poor, and 1 very poor. This method effectively reduces the limitations of enterprise comprehensive performance evaluation by introducing nonfinancial evaluation indicators.