基于不确定性测度的直觉模糊决策模型

在综合衡量直觉模糊数自身所具有的不确定性及其所表达信息的不确定性的基础上，以凸组合的形式设计了混合型直觉模糊熵和交叉熵测度；与已有测度相比，混合型熵测度具有更强的区分能力，而混合型交叉熵测度具有自然的对称性。在此基础上，设计了直觉模糊环境下的多属性群体决策模型，并将其应用于教育教学质量评价。理论分析和数值结果表明：混合型直觉模糊熵和交叉熵测度能够成对设计，互为印证，因而更具合理性；基于不确定性测度的群体决策模型结构清晰，步骤简明，决策结果客观有效。

Intuitionistic Fuzzy Decision Making Model Based on Uncertainty Measures

In this paper, some hybrid entropy and cross-entropy measures are designed in convex combinations for the intuitionistic fuzzy numbers (IFNs) on the basis of comprehensive consideration of their own uncertainty and the uncertainty of the information they express. Compared with the existing measures, the hybrid entropy measure has a stronger distinguishing ability and the hybrid cross-entropy measure possesses the natural symmetry. Based on this, a multi-attribute group decision-making model is developed under the intuitionistic fuzzy environment, and further applied to evaluation of the teaching quality. The theoretical analysis and numerical results show that the hybrid entropy and cross-entropy measures of the IFNs can be designed in pairs and mutually confirmed, which is more reasonable; with a clear structure and concise procedures, the group decision-making model based on these uncertainty measures can obtain an objective and effective result.