The robustness test results of the model.

<div><p>To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational risk theory, market risk, resea...

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Bibliographic Details
Main Author:	Xini Fang (20861990) (author)
Published:	2025
Subjects:	Biotechnology Immunology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified provides basic information experimental results show early warning strategies operational risk theory human resource risk enterprise risk assessment model &# 8217 45 %, 5 45 %, 4 09 %, 4 processing sample data handle complex data corporate operational risk traditional rf model improved rf model fcm clustering algorithm clustering algorithm rf algorithm risk indicators market risk financial risk development risk model achieves 95 %, 81 %, 29 %, 26 %, 20 %, rating data performance data fcm clustering data classification corporate bonds xlink "> weight method thereby enhancing response speed respectively 6 random forest primary indicators net value intercriteria correlation income products fuzzy c f1 score 48 %.
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The robustness test results of the model.

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