Research on sampling model of financial data sharing based on cloud service

Shuo Sun; Yue Geng; Chenlu Jia

doi:10.1117/12.2636677

6 May 2022 Research on sampling model of financial data sharing based on cloud service

Shuo Sun, Yue Geng, Chenlu Jia

Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121761Y (2022) https://doi.org/10.1117/12.2636677
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China

Abstract

With more and more uncertain factors affecting enterprise operation in market economy, enterprises are facing with more and more diversified risks. This requires accurate prediction of the future financial situation of the current enterprises in the market as far as possible, and take preventive measures in advance for the companies with hidden financial crisis. Based on the dynamic CBR model, this paper considers the influence of the year of the training sample in the current year, that is, the distance of the sample from the current year on the model's early warning performance, and builds a dynamic financial crisis early warning model with CBR as the basic classifier considering both concept drift and sample time weight. In this paper, the samples of the cloud financial sharing center of the current year are given a higher weight, while the samples of the distant year are given a lower weight. The results show that the prediction accuracy of THE CBR model considering the time weight of the sample has a stable improvement compared with the CBR model without considering the time weight of the sample.

Citation Download Citation

Shuo Sun, Yue Geng, and Chenlu Jia "Research on sampling model of financial data sharing based on cloud service", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121761Y (6 May 2022); https://doi.org/10.1117/12.2636677

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available