Four methods of approximate reasoning with interval-valued fuzzy sets
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Publication:1116711
DOI10.1016/0888-613X(89)90002-9zbMath0666.68083OpenAlexW2144989550MaRDI QIDQ1116711
Publication date: 1989
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0888-613x(89)90002-9
production planningapproximate reasoningmodus ponensinterval-valued fuzzy setSufficient conditionslinguistic connectives
Related Items (14)
Fuzzy sets in a approximate reasoning. I: Inference with possibility distributions ⋮ Meta-linguistic axioms as a foundation for computing with words ⋮ Four methods of approximate reasoning with interval-valued fuzzy sets ⋮ A representation of exponential form on fuzzy logic ⋮ Stability analysis and stabilization of fuzzy state space models ⋮ Uncertainty reasoning based on cloud models in controllers ⋮ Formalized theory of general fuzzy reasoning. ⋮ A review and comparison of six reasoning methods ⋮ Neuro-fuzzy clustering of radiographic tibia image data using type 2 fuzzy sets ⋮ Introduction to Fuzzy Systems ⋮ On the Incorporation of Interval-Valued Fuzzy Sets into the Bousi-Prolog System: Declarative Semantics, Implementation and Applications ⋮ Interval-Valued Degrees of Belief: Applications of Interval Computations to Expert Systems and Intelligent Control ⋮ The applications of interval-valued fuzzy numbers and interval-distribution numbers ⋮ Interval-valued fuzzy sets representation on multiple antecedent fuzzy \(S\)-implications and reasoning
Cites Work
- A model for the measurement of membership and the consequences of its empirical implementation
- Interval valued fuzzy sets based on normal forms
- Four methods of approximate reasoning with interval-valued fuzzy sets
- Feasible algorithms for approximate reasoning using fuzzy logic
- The concept of a linguistic variable and its application to approximate reasoning. III
- Measurement of membership functions and their acquisition
- Derivation of a Linear Decision Rule for Production and Employment
- Production Scheduling by the Transportation Method of Linear Programming
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