Suppose that we know the probability distribution corresponding to some property A. How can we then describe the distribution describing the negation of this property? In this paper, we show that, in general, we need additional information to uniquely determine the desired probability distribution. If we do not have this additional information and we still need to select one of the possible distributions for the negation, which one should we choose? We show that reasonable arguments lead to a formula proposed by Yager (IEEE Trans Fuzzy Syst 23(5):1899–1902, 2014). However, if we apply Yager’s formula to negation, we do not get the original distribution back. We show how to modify Yager’s formula so that the distribution for “not not A” will be the same as the original distribution for the property A.

假设我们知道对应于某些属性A的概率分布。那么，我们如何才能描述描述该属性取反的分布呢？在本文中，我们表明，一般而言，我们需要其他信息才能唯一确定所需的概率分布。如果我们没有这些额外的信息，而我们仍然需要为否定选择一种可能的分布，那么我们应该选择哪一种呢？我们证明，合理的论点导致了Yager提出的公式（IEEE Trans Fuzzy Syst 23（5）：1899–1902，2014）。但是，如果我们将Yager公式应用于求反，则不会获得原始分布。我们展示了如何修改Yager公式，以使“ not not A ”的分布”将与属性A的原始分配相同。