Introduction to non-linear optimization
Introduction to non-linear optimization
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Sum normal optimization of fuzzy membership functions
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Cluster Validation with Generalized Dunn's Indices
ANNES '95 Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems
A systematic approach to a self-generating fuzzy rule-table forfunction approximation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy sets of rules for system identification
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy rule-based classification systems
IEEE Transactions on Fuzzy Systems
Look-ahead based fuzzy decision tree induction
IEEE Transactions on Fuzzy Systems
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
Comparison of adaptive methods for function estimation from samples
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Constructing accurate fuzzy classifiers: A new adaptive method for rule-weight specification
International Journal of Knowledge-based and Intelligent Engineering Systems
Fuzzy logic-based embedded system for video de-interlacing
Applied Soft Computing
Rule base identification in fuzzy networks by Boolean matrix equations
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Tuning a fuzzy system to meet a given set of requirements is usually a difficult task that involves many parameters. Since doing it manually is often cumbersome, several CAD tools have been reported to automate this process. The tool we have developed, xfsl, tries to reduce the limitations of other tools. In this sense, it includes a wide set of supervised learning algorithms and is able to cope with complex fuzzy systems. In particular, xfsl is able to adjust hierarchical fuzzy systems; systems that employ fuzzy functions defined freely by the user, like membership or connective functions, defuzzification methods, or even linguistic hedges; and fuzzy systems with continuous outputs (such as fuzzy controllers) as well as categorical outputs (such as fuzzy classifiers). Several examples included in this paper illustrate all these issues. Another relevant advantage is that xfsl is integrated into the fuzzy system development environment Xfuzzy 3, and, hence, it can be easily employed within the design flow of a fuzzy system.