Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Rule-based modeling: precision and transparency
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
On generating FC3 fuzzy rule systems from data usingevolution strategies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Neural Networks
An Automated Hybrid CBR System for Forecasting
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Efficient and interpretable fuzzy classifiers from data with support vector learning
Intelligent Data Analysis
A fuzzy Actor-Critic reinforcement learning network
Information Sciences: an International Journal
Eliciting transparent fuzzy model using differential evolution
Applied Soft Computing
Efficient and interpretable fuzzy classifiers from data with support vector learning
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
A Hybrid Knowledge-Based Neural-Fuzzy Network Model with Application to Alloy Property Prediction
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Interpretability constraints for fuzzy information granulation
Information Sciences: an International Journal
Global and Local Modelling in Radial Basis Functions Networks
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
A decade of Kasabov's evolving connectionist systems: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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
So near and yet so far: New insight into properties of some well-known classifier paradigms
Information Sciences: an International Journal
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
Interpretability assessment of fuzzy knowledge bases: A cointension based approach
International Journal of Approximate Reasoning
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Fault fuzzy rule extraction from AC motors by neuro-fuzzy models
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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Radial basis function networks and fuzzy rule systems are functionally equivalent under some mild conditions. Therefore, the learning algorithms developed in the field of artificial neural networks can be used to adapt the parameters of fuzzy systems. Unfortunately, after the neural network learning, the structure of the original fuzzy system is changed and interpretability, which is considered to be one of the most important features of fuzzy systems, is usually impaired. This Letter discusses the differences between RBF networks and interpretable fuzzy systems. Based on these discussions, a method for extracting interpretable fuzzy rules from RBF networks is suggested. Simulation examples are given to embody the idea of this paper.