【摘要】 中智集作为模糊集的推广，有利于描述各种不确定、不一致、不连续的信息.针对单值中智集的三支决策分类结果单一缺陷，本文构建一种在区间中智集上的三支决策模型.首先，在单值中智集的定义上给出区间中智集的概念，根据贝叶斯决策理论和曼哈顿距离提出一种新的三支决策模型.然后，在区间中智集的信息系统中采用相似度计算条件概率得到期望损失，进一步建立区间中智集的三支决策模型.最后，通过医疗诊断实例具体阐述模型的应用，并讨论参数变化对决策结果的影响.更多还原

【Abstract】 As a type of generalization of fuzzy sets, neutrosophic sets are helpful to describe all kinds of uncertain, inconsistent and discontinuous information. Since the classification result of the three-way decision on a single-valued neutrosophic set is relatively unitary, a three-way decision model on an interval-valued neutrosophic set is constructed. Firstly, based on the definition of a single-valued neutrosophic set, the concept of an interval-valued neutrosophic set is given, and a new three-way decision model is proposed by combining Bayesian decision theory and Manhattan distance. Then, under the given similarity, the conditional probability is calculated to obtain the expected loss in the information system of the interval-valued neutrosophic set, and the three-way decision model of the interval-valued neutrosophic set is established. Finally, the application of new model is illustrated by an example of medical diagnosis, and the effects of parameter variations on decision results are discussed.更多还原