作为犹豫模糊集的扩展，概率犹豫模糊集能够更加准确和全面地表达复杂模糊环境下的决策信息。利用分布函数拟合概率犹豫模糊信息，并根据分布函数曲线覆盖面积的相异程度以及分布中心的差异，提出了一种新的距离测度。新距离测度能同时考虑概率犹豫模糊元素整体和内部可能值的差异程度，适合处理概率犹豫模糊信息数据量大的情形。基于新距离测度，能考虑决策者心理行为的TODIM决策方法被应用于概率犹豫模糊环境下属性权重未知的多属性决策问题。以在线会议软件的评估问题为案例分析，验证了方法的有效性。

As an extension of hesitant fuzzy sets, probabilistic hesitant fuzzy sets can express decision information in complex fuzzy environments more accurately and comprehensively. In this paper, by using distribution functions to fit probabilistic hesitant fuzzy information, a new distance measure is proposed based on the differences in the coverage areas and distribution centers of the distribution function curves. The new distance measure can simultaneously consider the degree of difference between the overall and internal possible values of probabilistic hesitant fuzzy elements, and is suitable for handling situations with large amounts of probabilistic hesitant fuzzy information data. Moreover, based on the new distance measure, the TODIM decision-making method that considers the psychological behavior of decision-makers, is applied to multi-attribute decision-making problems with unknown attribute weights under probabilistic hesitant fuzzy environments. A case study on the evaluation of online conference software verifies the effectiveness of the proposed method.