Zheng Yan, Qin Hongwu, Ma Xiuqin
College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, Gansu, China.
Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia.
Sci Rep. 2024 Mar 19;14(1):6562. doi: 10.1038/s41598-024-56922-5.
Interval-valued q-rung orthopair fuzzy set (IVq-ROFS) is a powerful tool for dealing with uncertainty. In this paper, we first propose a new method for aggregating multiple IVq-ROFSs, which is easier to understand and implement in the multi-attribute group decision making process compared to current aggregation operators. Secondly, this paper introduces a new fuzzy entropy with parameters based on IVq-ROFS, which is highly flexible due to its adjustable parameters. Based on this, the IVq-ROFS-based attribute weight calculation method is proposed to obtain the objective weights of the attributes, which is more reasonable and objective than the existing methods. Then, for the dimensional differences between the three compromise scores in the original Combined Compromise Solution (CoCoSo) method, the enhanced compromise scores are proposed. These scores are obtained by normalizing the three dependent compromise scores, ensuring that they fall within the same range. Finally, a novel CoCoSo mothed on IVq-ROFS using the proposed fuzzy entropy and enhanced compromise scores is presented. The proposed method is highly adaptable and scalable, not limited to IVq-ROFS. The excellent performance and robustness of the proposed method are verified in sepsis diagnosis applications.
区间值q阶正交对模糊集(IVq-ROFS)是处理不确定性的有力工具。本文首先提出一种聚合多个IVq-ROFS的新方法,与当前的聚合算子相比,该方法在多属性群决策过程中更易于理解和实现。其次,本文基于IVq-ROFS引入一种带参数的新模糊熵,由于其参数可调,具有高度灵活性。在此基础上,提出基于IVq-ROFS的属性权重计算方法以获得属性的客观权重,该方法比现有方法更合理、客观。然后,针对原始组合折衷解(CoCoSo)方法中三个折衷得分之间的维度差异,提出增强折衷得分。这些得分通过对三个相关折衷得分进行归一化得到,确保它们落在同一范围内。最后,提出一种基于IVq-ROFS的新型CoCoSo方法,该方法使用所提出的模糊熵和增强折衷得分。所提出的方法具有高度的适应性和可扩展性,不限于IVq-ROFS。该方法的优异性能和鲁棒性在脓毒症诊断应用中得到验证。