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Evidential Probabilities for Rough Set in a Case of Competitiveness

机译:竞争力粗糙集的证据概率

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Probabilistic rough set based on statistics and equivalence relations can provide membership, boundary approximations, subsets dependency, criterion dependency, three-way decision, and so forth. However, the probability is nondeterminant due to randomness and users' choices which is subjective in most cases. This research aims to provide determinant probabilities through relevant evidences on three-way decision, called evidential probabilities for rough set (EPRS) to consider the subjective criteria. In this article a research position highlights the boundary regions in terms of subjective criteria showing how subjective criteria may provide a means to narrow the uncertainty by projecting the boundary regions through user preferences in providing better decision precisions. The idea is also projected on prospect theory by showing the adaptable tuning of reference point through decision based subjective preferences. A case study about nations competitiveness is estimated through EPRS and shows the evidential probability can be identified in reality.
机译:基于统计数据和等效关系的概率粗糙集可以提供成员资格,边界近似,子集依赖性,标准依赖性,三元决策等。然而,由于随机性和用户的选择,在大多数情况下是主观的,概率是不确定的。本研究旨在通过对三元决策的相关证据提供决定性概率,称为粗糙集(EPRS)的证据概率,以考虑主观标准。在本文中,在主观标准方面,研究位置突出了边界区域,示出了主主主导标准如何通过在提供更好的决策芯片方面通过用户偏好投射边界区域来缩小不确定性的方法。通过基于决策的主观偏好显示参考点的适应性调整,还预测了前景理论的想法。通过EPRS估计关于国家竞争力的案例研究,并显示了可以在现实中识别的证据概率。

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