Affiliations: School of Economics and Management, Xiamen University of Technology, Xiamen, China
Correspondence:
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Corresponding author. Hongjie Lin, School of Economics and Management, Xiamen University of Technology, Xiamen, 316024, China. E-mail: lin800506@126.com.
Abstract: The goal of enterprise ERP is to select useful information and finally realize the goal of transforming information into enterprise competitiveness. At present, the research on the data quality optimization management of ERP system is not systematic enough, which can not achieve the effect of optimization management. In this paper, the author analyzes the enterprise ERP system optimization based on deep learning and dynamic fuzzy model. After dividing all kinds of typical activities of information process, this paper builds a model of information process of each ERP module with the method of information product diagram, which makes the invisible information production process visible, so as to realize the continuous improvement of information quality, and provides a complete set of optimized management methods and measures for enterprise information quality. The simulation results show that it is feasible to use neural network to solve the optimization design of the system. The main reason is that the variables among neural networks are distributed in parallel, and when the energy function tends to be stable, it can reach its minimum value, so as to achieve the purpose of optimization.
Keywords: Deep learning, neural network, enterprise ERP system, data quality
optimization
