Credit Risk Evaluation of Big Data Enterprises Based on Intuitionistic Fuzzy Sets

DOI

10.2991/aebmr.k.210409.008How to use a DOI?

Keywords

big data enterprises, credit risk, credit risk evaluation, intuitionistic fuzzy sets, intuitionistic fuzzy number

Abstract

The fuzzy sets theory cannot accurately reflect the hesitation or abstention of decision makers. In view of this problem, introducing the intuitionistic fuzzy sets, we put forward a credit risk evaluation model of big data enterprises based on intuitionistic fuzzy sets. Firstly, a credit risk evaluation index system of big data enterprises was constructed. Meanwhile, the intuitionistic fuzzy weights of indicators were determined with intuitionistic fuzzy AHP. Secondly, we constructed the IFWA operator, and then the intuitionistic fuzzy comprehensive evaluation value of sample enterprise was calculated. Finally, we used the score function of intuitionistic fuzzy number to calculate the credit comprehensive score and ranking of sample enterprise. Taking three listed companies in big data industry in China as sample, we used the above model to carry out an example analysis. The result of example analysis proves the feasibility and effectiveness of this model.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mu Zhang
AU  - Si-si Li
PY  - 2021
DA  - 2021/04/12
TI  - Credit Risk Evaluation of Big Data Enterprises Based on Intuitionistic Fuzzy Sets
BT  - Proceedings of the 9th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2020)
PB  - Atlantis Press
SP  - 54
EP  - 59
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210409.008
DO  - 10.2991/aebmr.k.210409.008
ID  - Zhang2021
ER  -