Logical entropy and aggregation of fuzzy orthopartitions

Fuzzy orthopartitions are generalizations of standard fuzzy partitions useful to model situations where both vagueness and uncertainty are involved. This work deepens the study of fuzzy orthopartitions lately started in [1], focusing on their lower and upper entropies. The latter subsume the concept of entropy in partition logic and measures the quantity of information contained in a fuzzy orthopartition. We mainly discover basic properties that characterize lower and upper entropies and highlight the connections between such entropy measures and novel operations and orderings on fuzzy orthopartitions introduced in this work.