Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
On Spohn's rule for revision of beliefs
International Journal of Approximate Reasoning
An introduction to fuzzy control
An introduction to fuzzy control
Distributed intelligent railway traffic control based on fuzzy decisionmaking
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Scheduling as a fuzzy multiple criteria optimization problem
Fuzzy Sets and Systems - Special issue on fuzzy multiple criteria decision making
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Fuzzy Optimization: Recent Advances
Fuzzy Optimization: Recent Advances
Fuzzy Mathematical Programming: Methods and Applications
Fuzzy Mathematical Programming: Methods and Applications
A general non-probabilistic theory of inductive reasoning
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Interval methods in knowledge representation
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Solving Large-Scale Fuzzy and Possibilistic Optimization Problems
Fuzzy Optimization and Decision Making
On Selecting an Algorithm for Fuzzy Optimization
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Computers & Mathematics with Applications
a fuzzy model for path delay fault detection
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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This paper presents a new approach to fuzzy modeling based on the concept of surprise. The new concept is related to the traditional membership function by an antitone transformation. Advantages of the surprise approach include: 1. It has a consistent semantic interpretation. 2. It allows the joint use of quantitative and qualitative knowledge, using simple rules of logic. 3. It is a direct extension of (and allows combination with) the least-squares approach to reconciling conflicting approximate numerical data. 4. It is ideally suited to optimization under imprecise or conflicting goals, specified by a combination of soft and hard interval constraints. 5. It gives a straightforward approach to constructing families of functions consistent with fuzzy associative memories as used in fuzzy control, with tuning parameters (reflecting linguistic ambiguity) that can be adapted to available performance data.