基于熵和改进的协相关度的直觉模糊决策方法

Intuitionistic fuzzy decision-making method based on entropy and improved co-correlation degree

针对决策信息为直觉模糊集且属性权重未知的多属性决策问题,以及关于协相关度的决策方法研究中存在的问题,提出了一种基于直觉模糊熵和改进的协相关度的决策方法。为准确度量直觉模糊集的直觉性和模糊性,给出了一种改进的直觉模糊熵的公式,概括并推广了原有的一类直觉模糊熵的公式,并讨论了其相关性质。然后由概率统计中相关系数的构造思想,改进了直觉模糊集协相关度的定义,构造了直觉模糊集与理想对象之间的相关系数以及得分函数,由此给出了一种改进的基于直觉模糊信息的多属性决策方法,最后通过实例计算验证了该方法的有效性和可行性。

Aiming at the multi-attribute decision-making problems with unknown attribute weight and Intuitionistic Fuzzy Set（IFS）as decision information, and the problems in researching decision-making methods on the basis of co-correlation degree, a decision-making method based on Intuitionistic Fuzzy（IF）entropy and modified co-correlation degree is proposed. In precise measurement of the intuitionism and fuzziness of IFS, a formula of improved IF entropy, which generalizes and extends the original formula of IF entropy, has been presented and adequately discussed. Moreover, from the structure of the correlation coefficient in probability statistics, the definition of co-correlation degree of IFS is improved by structuring the correlation coefficient and score function between IFS and ideal objects. Thus, an improved multi-attribute decision-making method based on intuitionistic fuzzy information is given, experimental results prove the effectiveness and feasibility.