Multiobjective Optimization in Linguistic Rule Extraction from Numerical Data
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Learning fuzzy rules from iterative execution of games
Fuzzy Sets and Systems - Theme: Modeling and learning
Extracting Interpretable Fuzzy Rules from RBF Networks
Neural Processing Letters
Online adaptive fuzzy neural identification and control of nonlinear dynamic systems
Autonomous robotic systems
Accuracy, comprehensibility and completeness evaluation of a fuzzy expert system
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Design of transparent mamdani fuzzy inference systems
Design and application of hybrid intelligent systems
International Journal of Approximate Reasoning
Development of scheduling strategies with Genetic Fuzzy systems
Applied Soft Computing
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Extracting symbolic knowledge from recurrent neural networks---A fuzzy logic approach
Fuzzy Sets and Systems
Evolutionary multiobjective fuzzy system design
Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
Looking for a good fuzzy system interpretability index: An experimental approach
International Journal of Approximate Reasoning
A new approach to fuzzy wavelet system modeling
International Journal of Approximate Reasoning
ACPOP: ambiguity correction-based pseudo-outer-product fuzzy rule identification algorithm
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
On advantages of scheduling using genetic fuzzy systems
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Generation of fuzzy membership function using information theory measures and genetic algorithm
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
FC4fuzzy rules system acquisition of complex system using interactive evolutionary computation
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
eFSM: a novel online neural-fuzzy semantic memory model
IEEE Transactions on Neural Networks
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Optimization of shared autonomy vehicle control architectures for swarm operations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
An information theoretic approach to generating fuzzy hypercubes for if-then classifiers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
International Journal of Approximate Reasoning
Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures
Information Sciences: an International Journal
A double axis classification of interpretability measures for linguistic fuzzy rule-based systems
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Optimization algorithm for learning consistent belief rule-base from examples
Journal of Global Optimization
Evolutionary generation of implicative fuzzy rules for design knowledge representation
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Engineering Applications of Artificial Intelligence
A novel belief rule base representation, generation and its inference methodology
Knowledge-Based Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium
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Sophisticated fuzzy rule systems are supposed to be flexible, complete, consistent and compact (FC3). Flexibility, and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violated if a fuzzy system is generated from data collected from real world applications. A systematic design paradigm is proposed using evolution strategies. The structure of the fuzzy rules, which determines the compactness of the fuzzy systems, is evolved along with the parameters of the fuzzy systems. Special attention has been paid to the completeness and consistency of the rule base. The completeness is guaranteed by checking the completeness of the fuzzy partitioning of input variables and the completeness of the rule structure. An index of inconsistency is suggested with the help of a fuzzy similarity which can prevent the algorithm from generating rules that seriously contradict with each other or with the heuristic knowledge. In addition, soft T-norm and BADD defuzzification are introduced and optimized to increase the flexibility of the fuzzy system. The proposed approach is applied to the design of a distance controller for cars. It is verified that a FC3 fuzzy system works very well both, for training and test driving situations, especially when the training data are insufficient