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A Linear Programming Method Based on Probabilistic Linguistic Kolmogorov-Smirnov Distance for Hospital Service Quality Evaluation

机译：基于概率语言Kolmogorov-Smirnov距离的线性规划方法用于医院服务质量评估

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摘要

Distance measures are important in the framework of multi-criterion decision making with probabilistic linguistic term sets. However, few studies investigated the distance of probabilistic linguistic term sets from the perspective of probability distributions. Due to this fact, this paper originally proposes a probabilistic linguistic Kolmogorov-Smirnov distance measure to identify the gaps between probability distributions. As a basis of this distance measure, the cumulative probability distributions of probabilistic linguistic term sets are introduced. Then, a common basic scale is given to get the probabilistic linguistic Kolmogorov-Smirnov distance between the probabilistic linguistic term sets with different lengths. After that, a linear programming technique for multidimensional analysis of preferences is developed based on the probabilistic linguistic Kolmogorov-Smirnov distance. An illustration of the hospital service quality evaluation is solved by the proposed method, and a sensitivity analysis is done to demonstrate the reliability of the results.
机译：距离措施在具有概率语言术语集的多标准决策框架中很重要。然而，很少有研究调查了从概率分布的角度来看概率语言术语集的距离。由于这一事实，本文最初提出了概率的语言Kolmogorov-Smirnov距离测量，以识别概率分布之间的间隙。作为该距离测量的基础，介绍了概率语言术语集的累积概率分布。然后，给出了普遍的基本规模，以获得具有不同长度的概率语言术语集之间的概率语言kolmogorov-smirnov距离。此后，基于概率语言Kolmogorov-Smirnov距离开发了一种用于多维偏好分析的线性规划技术。通过该方法解决了医院服务质量评估的图示，进行了敏感性分析来证明结果的可靠性。

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