Fuzzy modifiers based on fuzzy relations
Information Sciences—Informatics and Computer Science: An International Journal
Reasoning about Uncertain Contexts in Pervasive Computing Environments
IEEE Pervasive Computing
Service Adaptation Using Fuzzy Theory in Context-Aware Mobile Computing Middleware
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Situational computing: An innovative architecture with imprecise reasoning
Journal of Systems and Software
The Key Points of New Fuzzy Set Theory
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
A probabilistic fuzzy logic system for modeling and control
IEEE Transactions on Fuzzy Systems
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How to model situation user-friendly and precisely is a key issue for situation-aware applications. Fuzzy logic is an effective approach to model situation, but one obstacle is how to select the suitable operators between different fuzzy sets. One possibility is to combine the merit of both Fuzzy logic and Probability logic. The paper first introduces a set of constraints on conventional fuzzy logic and its operations, to setup a unified framework so as to combine the merits of the above two approaches. Such probabilistic-constrained fuzzy logic can be used in situation-aware applications. The paper then focuses on how to derive new fuzzy concepts from basic fuzzy partition, and how to compute the relationship between such derived and basic fuzzy concepts according to the probability constraints, which is different from the conventional ones.