Different approaches to induce cooperation in fuzzy linguistic models under the COR methodology
Technologies for constructing intelligent systems
Novel fuzzy logic control based on weighting of partially inconsistent rules using neural network
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Handling of inconsistent rules with an extended model of fuzzy reasoning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A proposal for improving the accuracy of linguistic modeling
IEEE Transactions on Fuzzy Systems
Selecting fuzzy if-then rules for classification problems using genetic algorithms
IEEE Transactions on Fuzzy Systems
Initial breeding value prediction on Manchego sheep by using rule-based systems
Expert Systems with Applications: An International Journal
International Journal of Approximate Reasoning
A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems
Expert Systems with Applications: An International Journal
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In this work we extend the Cooperative Rules learning methodology to improve simple linguistic fuzzy models, including the learning of rule weights within the rule cooperation paradigm. Considering these kinds of techniques could result in important improvements of the system accuracy, maintaining the interpretability to an acceptable level.