Novel Deng’s Grey Development Relation Model Based on Information Difference and Its Application in Sanatorium Performance Evaluation

Abstract

In view of the varying amounts of information and the difference in information value in sanatorium performance evaluation, Deng’s development relation model based on information difference is proposed herein. Firstly, the definition of panel data on sanatorium performance evaluation and the construction criteria of its optimal vector are given. Simultaneously, the indicators are standardized. In order to objectively highlight the difference of effective information among indicators, the entropy weight method is introduced to determine the weight of performance evaluation indicators in sanatoriums on the basis of traditional Deng’s correlation model avoiding the limitation of subjective effects. Furthermore, the weight of the temporal index is employed to determine the weight of performance evaluation results in different years, based on the new information priority, to dynamically evaluate the development trend of annual sanatorium performance. Finally, the performances of TS, YZ, and XZ sanatoriums are dynamically evaluated by using the proposed new grey relational model. Combined with the weight of time index, the 5-year comprehensive performance value is given. It is found that the performance level of TS sanatorium is the highest followed by YZ sanatorium and XZ sanatorium, which verifies the practicability and effectiveness of the model.

Multivariate Evaluation Method for Screening Optimum Gas-Sensitive Materials for Detecting SF6 Decomposition Products

“…(4) The final step is to determine the final score (φ IEM ) of the IEM method, which is presented as follows , where f ij (0,1) represents the normalized matrix to (0, 1). w j is the weight of entropy of the j -th index.…”

“…)/ j j j n j 1 (31) where 0 ≤ w j ≤ 1, and ∑ j=1 n w j = 1. (4) The final step is to determine the final score (φ IEM ) of the IEM method, which is presented as follows 21,23…”

“…Entropy means a measure of uncertainty, the more information, the less uncertainty and the less entropy, and vice versa. , According to the characteristics of entropy, the dispersion degree of an index can be judged by the entropy value. The greater the dispersion degree of the index, the greater the weight of the index on the comprehensive evaluation and the smaller the entropy value. − The variation coefficient method (VCM) is another statistic means to evaluate samples . Li et al have used this method to construct the comprehensive weighting vulnerability index model.…”