## 4 Materials and Results
### Results and Comparison  
The evaluation results and comparisons with other methods are shown in Table 6. It can be seen from Table 6 that the evaluation results of the proposed model are completely consistent with those of specifications and are almost consistent with other methods. This indicates that the intuitionistic connection cloud model based on an improved rough set used to assess the shrinkage-swelling grade is effective and feasible. The results of the comparative analysis also show that the accuracy of the proposed model reached 100%, while in the connection cloud model and normal cloud model, individual sample grade misjudgment occurred. For example, among the five index values of case A, \(C_{1}\) and \(C_{3}\) were in grade III, \(C_{2}\) was in grade IV, \(C_{4}\) was between grade II and III, and \(C_{5}\) was between grade III and IV; so, it was more reasonable to specify the shrinkage-swelling grade as grade III. Additionally, the intuitionistic connection degree takes into account the reliability of samples. This is conducive to coping with complex problems with numerous uncertain information. At the same time, the improved information entropy weighting method based on the rough set does not rely on any prior knowledge and can assign weight via objective data simultaneously considering the importance of the index. In general, an intuitionistic connection cloud model with universality and interpretability can deal with the interval-valued index containing multiple uncertainties and further characterize the hesitant characteristics of the problem relative to the traditional cloud models. These results also suggest that the application of the specification method may rely too much on the reliability of the parameters and cannot describe the uncertainty of information acquisition and cognitive uncertainty. However, the evaluation of the shrinkage-swelling grade will encounter subjective ambiguities, which is not conducive to the application of field engineers. In addition, various categories of uncertainty, such as fuzziness, ran \begin{table}
\begin{tabular}{l c c c c c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multicolumn{2}{c}{\(z\)**(x)**} & \multirow{2}{*}{**Cance**} & \multirow{2}{*}{**Cance**} & \multirow{2}{*}{**Cance**} & \multirow{2}{*}{**[PERSON]**} & \multirow{2}{*}{**[PERSON]**} & \multirow{2}{*}{**[PERSON]**} & \multirow{2}{*}{**[PERSON]**} & \multirow{2}{*}{**[PERSON]**} \\ \cline{2-2} \cline{5-6}  & **Grade** & & & & & & & & & **Expectation** \\  & **I** & **II** & **III** & **IV** & & & & & **Method** [10] \\ \hline A & 0.0000 & 0.0204 & 0.3543 & 0.0936 & III & IV & III & III & III \\ B & 0.0000 & 0.0002 & 0.0145 & 0.0570 & IV & IV & III & IV & IV \\ C & 0.0000 & 0.0000 & 0.0038 & 0.0947 & IV & IV & IV & IV & IV \\ D & 0.0000 & 0.0000 & 0.0036 & 0.0414 & IV & IV & IV & IV & IV \\ E & 0.0000 & 0.0000 & 0.0020 & 0.0876 & IV & IV & IV & IV & IV \\ F & 0.0000 & 0.0000 & 0.0013 & 0.0888 & IV & IV & IV & IV & IV \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Evaluation results and comparisons. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Index** & \(E_{x}\) & \(En_{\text{L}}\) & \(En_{\text{R}}\) & \(He\) & \(a_{\text{L}}\) & \(a_{\text{R}}\) & \(k_{\text{L}}\) & \(k_{\text{R}}\) \\ \hline \(C_{1}\) & 77.5 & 9.167 & 33.333 & 0.01 & 27.5 & 100 & 9.3217 & 1.2540 \\ \(C_{2}\) & 53.0 & 16.333 & 33.333 & 0.01 & 49.0 & 100 & 44.8877 & 2.4775 \\ \(C_{3}\) & 67.5 & 14.167 & 33.333 & 0.01 & 42.5 & 100 & 6.9729 & 1.6643 \\ \(C_{4}\) & 7.5 & 8.333 & 5.833 & 0.01 & 25.0 & 17.5 & 1.5537 & 2.2077 \\ \(C_{5}\) & 142.5 & 24.167 & 66.667 & 0.01 & 72.5 & 200 & 8.0698 & 1.5006 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Numerical characteristics of connection cloud for grade I.  
domness, and hesitation, may be inevitably encountered in evaluations, so the analysis of shrinkage-swelling grade cannot rely only on methods based on a single type of uncertainty.