Fuzzy Sets and Systems
Fuzzy complex analysis I: differentiation
Fuzzy Sets and Systems
Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Fuzzy limit theory of fuzzy complex numbers
Fuzzy Sets and Systems
Fuzzy complex analysis II: integration
Fuzzy Sets and Systems
Some remarks for fuzzy complex analysis
Fuzzy Sets and Systems
The Knowledge Engineering Review
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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Dealing with various inexact pieces of information has become an intrinsically important issue in knowledge-based reasoning, because many problem domains involve imprecise, incomplete and uncertain information. Indeed, different approaches exist for reasoning with inexact knowledge and data. However, the common strategy they adopt is to integrate various types of inexact information into a global measure. This may destroy the underlying semantics associated with different information components. This paper presents an innovative notion of fuzzy complex numbers (FCNs), which extends real complex numbers to representing two-dimensional uncertainties conjunctively without necessarily integrating them. This new framework is applied to supporting Compositional Modelling (CM). In particular, calculus of FCNs over arithmetic and propositional relations is developed to entail scenario model synthesis from model fragments, and modulus of FCNs is introduced to constrain the scenario descriptions. The utility and usefulness of this work are illustrated by means of an example for constructing possible scenario descriptions from given evidence in the crime investigation domain.