Intelligent financial decision support system based on data mining

Author:

Geng Chengxuan1,Xu Yunkai12,Metawa Noura34

Affiliation:

1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

2. School of Textile Apparel and Design, Changshu Institute of Technology, Suzhou, Jiangsu, China

3. College of Business Administration, American University in the Emirates, UAE

4. Faculty of Commerce, Mansoura University, Egypt

Abstract

With the development of information technology, intelligent control technology is the comprehensive application of modern management techniques and methods. This paper mainly studies the intelligent financial decision support system based on data mining. This paper mainly introduces data mining technology, an intelligent financial decision support system and the application of data mining technology in an intelligent financial decision support system. The intelligent financial decision support system proposed in this paper uses a relational database to store massive business data, to improve the system expansion ability. By using mathematical model and data mining technology, an intelligent financial decision support system can automatically analyze data, discover the internal relationship between data, and mine the model that plays an important role in prediction and decision-making behavior, to establish a new business model, help decision-makers to make marketing strategies in line with the market and make correct decisions. The experimental results show that: the actual total profit of the company in 2019 is 43.37 million yuan, and the predicted total profit in 2019 is 43.38 million yuan. The similarity between the actual total profit in 2019 and the predicted total profit in 2019 is 99.98%. In 2019, the company’s sales revenue is 37.61 million yuan. The predicted sales revenue in 2019 is 37.62 million yuan, which is 99.97% similar to the actual sales revenue in 2019. The managers of the company can make marketing strategies and make correct decisions according to the sales revenue forecast in 2020.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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