Fuzzy Modeling for Control
Hierarchical genetic fuzzy systems
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Advanced Fuzzy Systems Design and Applications
Advanced Fuzzy Systems Design and Applications
Accuracy Improvements in Linguistic Fuzzy Modeling
Accuracy Improvements in Linguistic Fuzzy Modeling
Margin based feature selection - theory and algorithms
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Eliciting transparent fuzzy model using differential evolution
Applied Soft Computing
A new methodology to improve interpretability in neuro-fuzzy TSK models
Applied Soft Computing
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new method for constructing membership functions and fuzzy rulesfrom training examples
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On generating FC3 fuzzy rule systems from data usingevolution strategies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Model generation by domain refinement and rule reduction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Will the real iris data please stand up?
IEEE Transactions on Fuzzy Systems
Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement
IEEE Transactions on Fuzzy Systems
GA-fuzzy modeling and classification: complexity and performance
IEEE Transactions on Fuzzy Systems
Compact and transparent fuzzy models and classifiers through iterative complexity reduction
IEEE Transactions on Fuzzy Systems
Fuzzy CoCo: a cooperative-coevolutionary approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Self-adaptive neuro-fuzzy inference systems for classification applications
IEEE Transactions on Fuzzy Systems
Data and feature reduction in fuzzy modeling through particle swarm optimization
Applied Computational Intelligence and Soft Computing
Expert Systems with Applications: An International Journal
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A novel approach to construct a set of interpretable and precise fuzzy systems based on the Pareto multi-objective cooperative co-evolutionary algorithm (PMOCCA) is proposed in this paper. Firstly, feature selection is used to reduce the dimensionality of the data in order to improve the performance and reduce computational burden. Secondly, the fuzzy clustering algorithm is employed to identify the initial fuzzy system. Thirdly, the PMOCCA is carried out to evolve the initial fuzzy system to optimize the number of rules, the antecedents of the rules and the parameters of the antecedents simultaneously. Furthermore, the interpretability-driven simplification techniques are used iteratively to reduce the fuzzy systems, thus the interpretability of the fuzzy systems is improved. Finally, the proposed approach is applied to benchmark problems, and the results show its validity.