The Pythagorean fuzzy sets are more robust than fuzzy sets and intuitionistic fuzzy sets in dealing with the problems involving uncertainty. To compare two Pythagorean fuzzy sets, distance measures play a crucial role. In this paper, we have proposed some novel distance measures for Pythagorean fuzzy sets using t-conorms. We have also discussed their various desirable properties. With the help of suggested distance measures, we have introduced some new knowledge measures for Pythagorean fuzzy sets. Through numerical comparison and linguistic hedges, we have established the effectiveness of the suggested distance measures and knowledge measures, respectively, over the existing measures in the Pythagorean fuzzy setting. At last, we have demonstrated the application of the suggested measures in pattern analysis and multi-attribute decision-making.

毕达哥拉斯模糊集在处理涉及不确定性的问题时比模糊集和直觉模糊集更健壮。为了比较两个毕达哥拉斯模糊集，距离测量起着至关重要的作用。在本文中，我们提出了一些使用 t-conorms 的勾股模糊集的新距离度量。我们还讨论了它们的各种理想特性。在建议的距离度量的帮助下，我们为毕达哥拉斯模糊集引入了一些新的知识度量。通过数值比较和语言对冲，我们分别建立了建议的距离度量和知识度量对勾股模糊设置中现有度量的有效性。最后，我们展示了建议措施在模式分析和多属性决策中的应用。