Results 211 to 220 of about 1,268 (239)

RULE BASED INTERPOLATING CONTROL - FUZZY AND ITS ALTERNATIVES

IFAC Proceedings Volumes, 1994
Abstract Design of control strategies based on heuristics is discussed. The most well-known example of this is fuzzy control. Fuzzy logic systems describe nonlinear mappings in terms of linguistic rules and an interpolative reasoning method. A useful tool for understanding advances in fuzzy control is proposed by considering the similarity between a ...
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Hierarchical Bidirectional Fuzzy Rule Interpolation and Rule Base Refinement

2018
For many practical intelligent decision-making applications, the “curse of dimensionality” is a serious problem; that is, the number of rules increases exponentially along with the number of input variables to the fuzzy inference system (Raju G, Zhou J, Roger A (1991) Int J Control 54(5):1201–1216 [1]).
Shangzhu Jin, Qiang Shen, Jun Peng
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Practical Aspects of Fuzzy Rule Interpolation

2014
The number of the Fuzzy Rule Interpolation (FRI) applications in engineering tasks is still insignificant compared to the classical fuzzy reasoning methods. The main goal of this paper is to emphasize the benefits of the direct (embedded) applicability of fuzzy rule interpolation and the related sparse rule-based knowledge representation through ...
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Interpolation in homogenous fuzzy signature rule bases

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017
Fuzzy signature sets (FSigSets) are extensions of the original fuzzy set concept, and also of the Vector Valued Fuzzy Set notion. In a FSigSet rule base the (input) universe of discourse X is mapped into a set of hierarchically grouped fuzzy sets, and each element of X has a “membership degree” consisting of a rooted tree with membership degrees at ...
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An Alternative Backward Fuzzy Rule Interpolation Method

International Journal of Software Science and Computational Intelligence, 2014
Fuzzy set theory allows for the inclusion of vague human assessments in computing problems. Also, it provides an effective means for conflict resolution of multiple criteria and better assessment of options. Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in sparse rule-based ...
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Guiding Fuzzy Rule Interpolation with Information Gains

2016
Fuzzy rule interpolation enables fuzzy systems to perform inference with a sparse rule base. However, common approaches to fuzzy rule interpolation assume that rule antecedents are of equal significance while searching for rules to implement interpolation. As such, inaccurate or incorrect interpolated results may be produced.
Fangyi Li, Changjing Shang, Ying Li, Qiang Shen   +3 more
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Extending the Fuzzy Rule Interpolation "FIVE" by Fuzzy Observation

2006
Some difficulties emerging during the construction of fuzzy rule bases are inherited from the type of the applied fuzzy reasoning. In fuzzy systems, when classical methods (e.g. the Compositional Rule of Inference) are applied, the completeness of the fuzzy rule base is required to generate meaningful output. This means, that the fuzzy rule base has to
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Fuzzy Rule-Based Classification Method for Incremental Rule Learning

IEEE Transactions on Fuzzy Systems, 2022
Niu, Degang Chen, Jinhai Li
exaly  

Fuzzy rule interpolation and benchmark system

2021
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Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases

2001
Mayuka F. Kawaguchi, Masaaki Miyakoshi
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