## 3 Results and Discussion
Each curve in Figure 3 corresponds to one of the four chosen universities; hence, only a sort of third-order Fourier series expansion with a high R-square (from 0.90 to 0.99) is fitted. These curves represent a regular pattern of activity, from which a wide variety of inferences can be inferred, which are briefly discussed below:- For IUST, as the number of quality criteria increased, the slope of the curve fell, indicating that the university's performance decreased. One of the reasons is that this university paid close attention to some criteria while paying little attention to others. Another reason for this behavior is the AHP-TOPSIS model's relative comparison of criteria. - The behavior of the SU and KUT is in direct opposition to one another, as seen by this figure, which is also in agreement with Figure 3. That is, students might select one of these two universities based on the importance of their desired criteria. - The most fluctuations, as shown in the previous figure, occur at AUT. That is, changing the quantity and kind of quality criteria has a significant impact on the relative closeness coefficient. - The fluctuating trend of the relative-closeness coefficients at AUT is regular, intense, and has a short-wave height. This ensures that, despite the high sensitivity of the quality criteria, quality control is carried out correctly and on time. - The fluctuating pattern of the relative-closeness coefficients is generally mild for SU and KUT, with multiple wavelengths but normal wave heights. This is because, practically, all criteria are taken into consideration, although this attention to the criterion is not particularly high. Furthermore, the shifting tendency at these two universities is diametrically opposed because specific criteria in one university receive more attention than in the other. Figure 4 shows the changes in the relative closeness coefficients for the removal of only one of the quality criteria (except the removal of criterion 1) for four universities. The curves shown were fitted by second-order Fourier series expansion with a high correlation coefficient between 0.85 and 0.97. This figure leads to the following findings:  
Figure 3: Analyzing the changes in education quality across four universities based on relative-closeness coefficients and number of criteria (Table 5). - The values on the vertical axis in this figure range from 0.2 to 0.7, while those in Figure 3 range from 0 to 1. This indicates that, in general, the relative-closeness coefficients decrease as the number of criteria increases due to the relative nature of the comparisons and the systematic influence of the criteria on each other. - The highest and lowest curves generally represent IUST and KUT, respectively, and as a result, they have the highest and lowest relative-closeness coefficients. This study provides a comprehensive examination of some Iranian universities. It is important to highlight that these cases not only generate significant interest among beneficiaries, including civil engineering students but also shed light on the impact of decision support systems on decision-making processes. Additionally, they foster a sense of active engagement in real-world political scenarios [77, 80].