I am currently in the final year of my BSMS course in mathematics. I am working on neutrosophic sets, primarily a generalization of intuitionistic fuzzy sets that was introduced by F. Smarandache in 1999, and their application to decision-making. I have been reading about the correlation of neutrosophic sets by Jun Ye (see the attachment named "Correlation of SVNS"). In the same paper, I came across a concept called "informational energy," which traces back to the informational energy of intuitionistic fuzzy sets, which was introduced by T. Gerstenkorn and J. Manko (see page 40, section 2 of the attachment named "Correlation measure of IFS"). As the authors mentioned, the concept of informational energy in the context of fuzzy set theory was initiated by D. Dumitrescu in his paper: Dumitrescu, D., A definition of an informational energy in fuzzy sets theory, Studia Univ. Babeş-Bolyai Math. 7,2 (1977) 57–59. But I could not find the paper online. Also, I couldn't find a subsequent paper that explains the idea clearly. Consequently, I am not sure of the intuition behind defining this concept!

However, from what I understand, the notion of informational energy is related to the notion of covariance in statistics. Gerstenkorn and Menko suggested a formula to compute the informational energy of a fuzzy set that resembles the "inner product" of two "vectors." This is consistent with the fact that covariance is indeed the L2-inner product defined on the L2-subspace of the vector space L0 formed by random variables of zero mean and finite variance. Furthermore, we know that covariance is a measure of the joint variability of two random variables. The sign of which shows the tendency in the linear relationship between the variables. And zero covariance corresponds to uncorrelated random variables. Therefore, I am sure that there must be some similar insight into the informational energy of a fuzzy set that I am failing to see. What does it measure, basically?

Kindly help me realize the same. Or any relevant reference will be highly appreciated. Thanks for bearing with me!