Research on Enterprise Economic Risk Forecast Model Based on Big Data Fusion

• Published in: 2020 International Conference on Big Data and Informatization Education (ICBDIE) pp. 5 - 9
• Main Author: Wang, Tao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2020
• Subjects: Analytical models; Big Data Fusion; component; Data mining; Data models; Economics; Enterprise economy; Feature extraction; prediction model; Predictive models; Risk management; Risks
• DOI: 10.1109/ICBDIE50010.2020.00009

In order to improve the capability of enterprise economic risk assessment and prediction, this paper combines panel data analysis method to construct enterprise economic risk prediction model, proposes enterprise economic risk prediction model based on big data fusion, establishes fusion clustering model of enterprise economic risk assessment panel data, and uses fuzzy correlation fusion clustering method to make statistical analysis of enterprise economic risk assessment panel data. Quantitative regression analysis and fuzzy clustering methods are used for panel data mining of enterprise economic risk assessment, adaptive block feature matching in the risk prediction process is carried out according to the mining results of panel data bureau, interference suppression in the enterprise economic risk prediction process is carried out by using correlation feature matching method, large data fusion in the enterprise economic risk prediction process is carried out by combining fuzzy information clustering and statistical analysis methods, and optimization of enterprise economic risk prediction is realized according to the rule distribution relation of recursive entropy. The simulation results show that the method has high accuracy in predicting the economic risks of enterprises, improves the data mining and information fusion capabilities of enterprises' economic risks, and improves the anti-risk capability of enterprises.