## 5 Conclusions  
In this study, an algorithm for parameter identification of concrete pavement structures has been presented. SEM was used as the forward algorithm for the dynamic responses of layered pavement structures, and the time-history curve of the pavement deflection basin displacement responses under FWD loads was obtained. The accuracy of the forward algorithm was verified via a comparison with the existing literature. Based on this, the CNN was adopted, and the deflection basin displacement time-history curves were taken as the input condition to establish a numerical model for the parameter identification of layered pavement structures. The main conclusions of this research are as follows.  
1. Compared with inversion using the peak values of the pavement deflection basin displacement as the input condition, more accurate inversion results can be obtained by using the entire time-history curves of the pavement deflection basin displacement as the input condition. The phenomenon of \"modulus transferring\" is avoided, as well as the non-unique problem.
2. With the increase in the number of samples, the accuracy of the inversion results increases gradually. For the inversion model of the dynamic modulus of the three-layer pavement structure, when the number of training samples reached 950, the RMSE was only 0.0417, which proves the high accuracy of the proposed inversion algorithm. For the inversion of the dynamic modulus of the pavement structure, the MAPE of the inversion results was found to be basically controlled within 4.11%, and the MAPE of the inversion results of the base and subbase layers were also basically controlled within 3.34%. Thus, inversion results were found to have adequate numerical stability.
3. The algorithm can also be used for the inversion of the thickness and dynamic modulus of the pavement structure layer. As the number of inversion variables increases, the inversion accuracy will decline to a certain extent. The algorithm in this paper is of a high solution accuracy for the inversion of the dynamic elastic modulus of the pavement structure surface. The average relative error of the inversion results is basically controlled within 8%, while the inversion accuracy for the thickness is relatively low. The average relative error of the inversion results is basically controlled within 12%, and the inversion results have adequate numerical stability.
4. The limitation of this study is that the contact boundary conditions between the pavement structure and the subgrade are not considered, and all the results obtained are purely simulation results without considering the impact of noise. Previous research shows that the interface between the pavement structure and the subgrade will have a certain degree of relative slip, which has a certain impact on the dynamic response of the pavement surface. Therefore, the inversion accuracy of pavement structure dynamic modulus will also be affected. The contact boundary conditions  
Figure 13: Comparison between the predicted and exact depth of the testing samples. (**a**) Thickness of the first layer of the pavement structure; (**b**) Thickness of the second layer of the pavement structure; (**c**) Thickness of the third layer of the pavement structure.  
will be considered in future research, and the proposed algorithm will be applied to the actual tests and engineering practice.  
Methodology, G.C. and Z.H.; Software, X.C. and L.Y.; Validation, X.C. and L.Y.; Investigation, D.B.; Data curation, X.C. and L.Y.; Supervision, D.B.; Funding acquisition, D.B. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Guangdong Province Universities and Colleges Characteristic Innovation Project of China (2022 KTSCX171).  
Not applicable.  
**Data Availability Statement**: Some or all data, models, or codes generated or used during the study are available from the corresponding author by request.  
The authors declare no conflict of interest.