Application research of machine learning method based on DBN and RL in financial data analysis

Abstract

With the continuous development of various emerging information technologies such as big data, cloud computing, artificial intelligence and machine learning, many traditional enterprises are actively cross-integrating with it, especially financial enterprises. For example, the background of big data is used to help transform financial accounting into management accounting [1]; The application of Python in financial data mining and analysis [2]. In addition, machine learning technology also has a deeper application in the field of financial data analysis, and many experts and scholars have also studied the importance of machine learning technology in financial data analysis. For example, Cheng Ping, Yu Chang, Wang Jianjun et al. have elaborated on the intelligent early warning of enterprise internal audit based on deep self-coding network in the GhatGDP era [3] and so on. These research results highly confirm the promoting role of machine learning methods in the field of financial data analysis, and further stimulate people's enthusiasm to use machine learning methods to improve financial data analysis. In this paper, by studying the application of machine learning methods based on DBN and RL in financial data, the advantages of deep belief neural network and reinforcement learning are combined to provide a more efficient method for enterprise financial data analysis.