Early warning of enterprise finance risk of big data mining in internet of things based on fuzzy association rules

As the big data, Internet of Things, cloud computing, and other ideas and technologies are integrated into social life, the big data technology can improve the corporate financial data processing. At the same time, with the fiercer competition between enterprises, investors and enterprises have paid more attention to the role of financial crisis warning in corporate management. The work selected the multiple financial indicators based on big data mining in Internet of Things. The rules between all financial indicators were found to choose more representative financial risk indicators. Then the frequent fuzzy option set was determined by FCM (fuzzy cluster method), parallel rules, and parallel mining algorithm, thus obtaining the fuzzy association rules that satisfy the minimum fuzzy credibility. Finally, the relevant data of listed companies were selected to analyze the corporate financial risks, which verified the method proposed in the work.

Automated summary

With the integration of big data, Internet of Things, and cloud computing into social life, the importance of financial crisis warning in corporate management is increasing. This study used big data mining technology to select multiple financial indicators in the Internet of Things, and determined fuzzy association rules using the FCM and parallel mining algorithm. The method proposed in the study was verified by analyzing corporate financial risks using data from listed companies.