## 4 Discussion  
Combined with the 21 evaluation indicators of UUSR comprehensive quality given above, UUSR evaluation results using traditional entropy weight method and E-TW are carried out separately. It is necessary to verify the stability of the E-TW model and compare it with the entropy weight method for the accuracy of UUSR evaluation results. Therefore, the basic data sets of years \(T_{1}\) and \(T_{2}\) of the six urban areas of a city are virtually constructed for experimental calculation with uniform trends of change, and the data set of year \(T_{2}\) is assumed to be the recent data. Considering the slightly important situation of recent data, the time degree \(\lambda\) is selected as 0.4 based on the weighting method of time dimension. The time weighting vector calculated by Equation (7) is expressed as \(W^{t}=\big{(}w_{T_{1}}^{t},w_{T_{2}}^{t}\big{)}=(0.4,\,0.6)\). Furthermore, the UUSR evaluation results (Figure 2) are obtained respectively based on the multi-objective linear weighting mathematical model.  
As shown in Figure 2, since the virtual construction data of area 1 to area 6 shows a monotonically increasing trend, the evaluation results of area 1 and area 6 are 0 and 1, respectively, because the data are standardized by using the extreme value method. Meanwhile, the evaluation results of areas 1, 2, 3, 4, 5, and 6 increase monotonically, and have strong consistency and nice calculation effects, when the UUSR evaluation is carried out by using the same weighting method, regardless of the entropy weight method or the E-TW model, which includes the time weighted preposition method and time weighted postposition method. The entropy weight method is a recognized method used in UUSR evaluation. In view of the similar consistency and calculation effect, it is reasonable for the E-TW model to be utilized in UUSR evaluation.  
In addition, the degree of dispersion \(D_{i}=\frac{1}{N-1}\sum R_{ij}\) is used to measure the advantages and disadvantages of the UUSR evaluation results from utilizing different weighting methods, where \(N\) is the total number of UUSR evaluation results using different weighting methods and \(R_{ij}\) is the Euclidean distance between UUSR evaluation results, assuming \(R_{ij}=0\) between the same type of results. Particularly, it indicates that the evaluation result is more reasonable than other results when the degree of dispersion is smaller.  
As shown in Table 3, the degrees of dispersion have been calculated with very different results when using the entropy weight method and the E-TW model. In detail, the results are arranged in order from small to large: \(D_{\text{TW}_{\text{post}}}<D_{\text{TW}_{\text{pre}}}<D_{\text{Entropy}_{T_{2 }}}<D_{\text{Entropy}_{T_{1}}}\). As the different types of N-TW model, the degree of dispersion calculated by time weighted preposition method \(D_{\text{TW}_{\text{post}}}\) is approximately equal to 0.005157118, that is, almost the same as \(D_{\text{TW}_{\text{pre}}}\) which is equal to 0.005157122, approximately. Nevertheless, the degrees of dispersion of time weighted postposition method and time weighted preposition method are much smaller than those of the entropy weight method in different moments. Obviously, the hybrid weight assignment model, regardless of the time weighted preposition method or time weighted postposition method, is a suitable and reasonable weighting model for UUSR evaluation in this research.