Application of improved RBF neural network algorithm in hierarchical management of enterprise

Abstract

Abstract The grade division of enterprises is conducive to their needs of green development, and the continuous strengthening of computer innovation technology provides an excellent platform for grading the regional management of enterprises. Owing to the differences in energy consumption, labour, land use area, GDP, etc., most of the data collected by the enterprises are unstable, and the data with a small number of samples in categories cannot be ignored. Therefore, based on the related data of basic development in a development area, Guangdong Province within the past 15 years, in this paper, according to the theory of hierarchical management in enterprise, four factors, such as land use, personnel, energy consumption and regional GDP, are used as the relevant attributes, and the grades of enterprises in this region are managed and divided. In addition, the structure of RBF neural network algorithm optimised by similarity relation matrix and the accuracy of enterprise classification under different neural network algorithms are compared. The results show that the hierarchical management of enterprises based on the improved RBF neural network algorithm has high efficiency and accuracy, which is of great significance to the green development of enterprises.