**6. Discussion and Conclusions**

Researchers have proposed different prediction models for PE and IC debonding and these models for predicting PE and IC debonding have facilitated the study of the debonding failure of FRP-strengthened RC beams. Still, they have significant coefficients of variation between the calculated and experimental values.

This paper used correlation analysis and grey correlation analysis to construct the indicator system for debonding failure. PE and IC debonding prediction models for FRP-strengthened RC beams were developed by several machine learning algorithms. Optimization of the model took place using the Dung Beetle Optimizer and comparison with the model suggested by codes. We can draw the following conclusions:


**Author Contributions:** Conceptualization, methodology, software, validation, writing—original draft, writing, T.H.; supervision, funding acquisition, writing, H.Z.; funding acquisition, supervision, J.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was supported by the National Natural Science Foundation of China (52278291), and the Chongqing Natural Science Foundation of China (CSTB2022NSCQ-LZX0006, cstc2020jcyjjqX0006, cstc2022ycjh-bgzxm0086).

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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