## 5 Conclusions  
To address the problem that the influence of the time dimension is not taken into consideration in the UUSR evaluation, a hybrid weight assignment model named entropy and time weighting model (E-TW) for UUSR evaluation is proposed by integrating the classic entropy weight method with the weight method of time dimension. This paper allows for several conclusions. First, the E-TW model can simultaneously reflect the impact of the indicator dimension and time dimension on the UUSR evaluation by combining the weighting methods of the two types of dimensions. Second, as the different order of the time weights used in the weighting process, the E-TW model is subdivided into two kinds of methods using the same TOWA operator, including the time weighted preposition method and the time weighted postposition method. Third, the evaluation results of the six areas increase monotonically and have strong consistency and nice calculation effects, when they are carried out by using the same weighting method, regardless of the classic entropy weight method or the E-TW model. Fourth, the hybrid weight assignment model, regardless of the time weighted preposition  
Figure 2: The UUSR evaluation results using different weighting methods.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \(R_{ij}\) & \(\text{Entropy}_{T_{1}}\) & \(\text{Entropy}_{T_{2}}\) & \(\text{TW}_{\text{pre}}\) & \(\text{TW}_{\text{post}}\) & \(D_{i}\) \\ \hline Entropy\({}_{T_{1}}\) & 0 & 0.0149 & 0.0084 & 0.0090 & 0.0108 \\ Entropy\({}_{T_{2}}\) & 0.0149 & 0 & 0.0065 & 0.0060 & 0.0091 \\ TW\({}_{\text{pre}}\) & 0.0084 & 0.0065 & 0 & 0.0005 & 0.0052 \\ TW\({}_{\text{post}}\) & 0.0090 & 0.0060 & 0.0005 & 0 & 0.0052 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The degree of dispersion of different weighting methods.  
method or time weighted postposition method, is a suitable and reasonable weighting model for UUSR evaluation because of the degrees of dispersion are much smaller than those of the entropy weight method in different moments.  
This study made an attempt to introduce a hybrid weight assignment model into the UUSR evaluation. However, the E-TW model contains two weight components of different dimensions, that is, the entropy weight of indicator dimension and the weight of time dimension. Due to their respective calculation principles, the utilization of the E-TW model has some limitations. In detail, for the entropy weight method, its weight calculation depends on the data of evaluation indicators, but the data may not be easy to obtain and collect completely. Besides, for the weight of time dimension, its weight calculation depends on the suitable time degree (\(\lambda\)), but the \(\lambda\) is often determined by the literature and the opinions of experts. Therefore, several aspects of this research need to be developed further, such as verifying the applicability and rationality of the E-TW model in the real case. In addition, the combination of different weighting methods using in UUSR evaluation and the cross application of weight assignment models of other disciplines need to be fully analyzed to improve the extant weighting methods based on future researches.  
Conceptualization, D.L. and L.W.; methodology, D.L.; software, D.L.; validation, D.L., L.W. and Y.Y.; formal analysis, D.L.; investigation, Y.Y.; resources, L.W.; data curation, Y.Y.; writing--original draft preparation, D.L.; writing--review and editing, L.W.; visualization, D.L.; supervision, L.W.; project administration, L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript. This research was funded by the Central South University Innovation Leadership Talents Project under grant number 506030101, and Huxiang High-level Talents Aggregation Project Innovation Talents Project under grant number 2018 RS3013. The authors declare no conflict of interest.