Results 261 to 270 of about 96,386 (319)
Some of the next articles are maybe not open access.
Size reduction by interpolation in fuzzy rule bases
IEEE Transactions on Systems, Man, and Cybernetics, 1997Fuzzy control is at present still the most important area of real applications for fuzzy theory. It is a generalized form of expert control using fuzzy sets in the definition of vague/linguistic predicates, modeling a system by If...then rules. In the classical approaches it is necessary that observations on the actual state of the system partly match (
L T Koczy
exaly +3 more sources
Linear fuzzy rule base interpolation using fuzzy geometry
International Journal of Approximate Reasoning, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Suman Das, Debjani Chakraborty
exaly +2 more sources
Approximate reasoning with fuzzy rule interpolation: background and recent advances
Artificial Intelligence Review, 2021 Approximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then rules in which attribute values are imprecisely described. Fuzzy rule interpolation (FRI) supports such reasoning with sparse rule bases where certain observations ...
Changjing Shang, Ying Li, Qiang Shen
exaly +2 more sources
A New Approach for Transformation-Based Fuzzy Rule Interpolation
IEEE Transactions on Fuzzy Systems, 2020 Fuzzy rule interpolation (FRI) is of particular significance for reasoning in the presence of insufficient knowledge or sparse rule bases. As one of the most popular FRI methods, transformation-based fuzzy rule interpolation (TFRI) works by constructing ...
Tianhua Chen +2 more
exaly +2 more sources
Fuzzy Rule Interpolation with A General Representation of Fuzzy Sets
2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)Fuzzy interpolative reasoning offers an important method to perform fuzzy inference in sparse fuzzy rule-based systems and helps to reduce the complexity of completed fuzzy systems. A number of fuzzy interpolative reasoning methods have been proposed for
Yanpeng Qu +3 more
openaire +2 more sources
Similarity Function-Assisted Dynamic Fuzzy Rule Interpolation: An Improved Approach
IEEE International Conference on Fuzzy Systems, 2023Fuzzy rule interpolation (FRI) enables fuzzy inference systems to derive consequences when the observations are not covered by a system's sparse rule base.
Ruilin Xu +3 more
semanticscholar +1 more source
IEEE International Conference on Fuzzy Systems, 2023
Fuzzy rule interpolation (FRI) provides an innovative approach to deducing conclusions for observations that do not match existing rules in a sparse fuzzy rule base.
Jinle Lin +3 more
semanticscholar +1 more source
Fuzzy rule interpolation (FRI) provides an innovative approach to deducing conclusions for observations that do not match existing rules in a sparse fuzzy rule base.
Jinle Lin +3 more
semanticscholar +1 more source
IEEE transactions on fuzzy systems, 2021
Formulating a generalized monotone fuzzy rule interpolation (MFRI) model is difficult. A complete and monotone fuzzy rule-base is essential for devising a monotone zero-order Takagi–Sugeno–Kang (TSK) fuzzy inference system (FIS) model.
Yi Wen Kerk, K. Tay, C. Lim
semanticscholar +1 more source
Formulating a generalized monotone fuzzy rule interpolation (MFRI) model is difficult. A complete and monotone fuzzy rule-base is essential for devising a monotone zero-order Takagi–Sugeno–Kang (TSK) fuzzy inference system (FIS) model.
Yi Wen Kerk, K. Tay, C. Lim
semanticscholar +1 more source
Demonstration of expert knowledge injection in Fuzzy Rule Interpolation based Q-learning
IEEE/SICE International Symposium on System Integration, 2021The learning phase of the traditional reinforcement learning methods can be started without any preliminary knowledge about the problem needed to be solved. The problem related knowledge-base is built based on the reinforcement signals of the environment
T. Tompa +3 more
semanticscholar +1 more source
Dynamic Fuzzy Rule Interpolation and Its Application to Intrusion Detection
IEEE Transactions on Fuzzy Systems, 2018 Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in sparse rule-based systems (and also for reducing the complexity of fuzzy models).
Nitin Naik, Ren Diao, Qiang Shen
exaly +2 more sources