Generally, in every decision-making process under the fuzzy domain, ranking of fuzzy numbers is indispensable. Although such approaches are abundant, yet a universally accepted approach is not apparent. Hence, newer methodologies have been developed since its inception. In many instances, defuzzification techniques are being criticized as these methodologies are based on intuition and the geometry of the fuzzy numbers. Furthermore, in many instances the reasonable properties that a ranking method should follow are not being verified. However, in the current study, a novel defuzzification technique is being developed with the notion of value and multiple of a ambiguity inclusion-exclusion function, $𝜃$, with ambiguity at various decision levels. The current method perfectly obeys the intuition and the geometry of the fuzzy numbers. Adding to this, it should be emphasized that the current methodology follows all the reasonable properties of a ranking method. Furthermore, new properties are stated and proved which illustrate the novelty of the present method. Furthermore, the shortcomings and drawbacks of the existing methods are overcome by the current methodology. Noteworthy, the current method ranks the fuzzy numbers and their corresponding images consistently, which was not evident in most of the existing methods.

一般来说，在模糊域下的每一个决策过程中，模糊数的排序都是必不可少的。尽管此类方法很多，但普遍接受的方法并不明显。因此，从一开始就开发了更新的方法。在许多情况下，去模糊化技术受到批评，因为这些方法基于直觉和模糊数的几何形状。此外，在许多情况下，排名方法应遵循的合理属性并未得到验证。然而，在目前的研究中，正在开发一种新的去模糊化技术，其概念是模糊包含排除函数的值和倍数，$𝜃$，在不同的决策层面都存在歧义。当前的方法完全符合直觉和模糊数的几何学。除此之外，应该强调的是，当前的方法遵循排名方法的所有合理属性。此外，陈述并证明了新的性质，说明了本方法的新颖性。此外，当前方法克服了现有方法的缺点和不足。值得注意的是，当前的方法对模糊数字及其对应的图像进行一致的排序，这在大多数现有方法中并不明显。