Structure identification of fuzzy model
Fuzzy Sets and Systems
A review and comparison of six reasoning methods
Fuzzy Sets and Systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Completeness and consistency conditions for learning fuzzy rules
Fuzzy Sets and Systems
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Rough-Fuzzy MLP: Modular Evolution, Rule Generation, and Evaluation
IEEE Transactions on Knowledge and Data Engineering
Rule base reduction: some comments on the use of orthogonal transforms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Similarity measures in fuzzy rule base simplification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Simplifying fuzzy rule-based models using orthogonal transformationmethods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
POPFNN-AAR(S): a pseudo outer-product based fuzzy neural network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Input features' impact on fuzzy decision processes
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Selection of relevant features in a fuzzy genetic learningalgorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolving fuzzy neural networks for supervised/unsupervised onlineknowledge-based learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Combinatorial rule explosion eliminated by a fuzzy rule configuration
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
A proposal for improving the accuracy of linguistic modeling
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
Neuro-fuzzy rule generation: survey in soft computing framework
IEEE Transactions on Neural Networks
GenSoFNN: a generic self-organizing fuzzy neural network
IEEE Transactions on Neural Networks
A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
A nature inspired Ying-Yang approach for intelligent decision support in bank solvency analysis
Expert Systems with Applications: An International Journal
Ovarian cancer diagnosis with complementary learning fuzzy neural network
Artificial Intelligence in Medicine
HebbR2-Taffic: A novel application of neuro-fuzzy network for visual based traffic monitoring system
Expert Systems with Applications: An International Journal
A new method for design and reduction of neuro-fuzzy classification systems
IEEE Transactions on Neural Networks
Fuzzy associative conjuncted maps network
IEEE Transactions on Neural Networks
A hypothalamic and piagetian fuzzy inference system: HtPFIS
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
eFSM: a novel online neural-fuzzy semantic memory model
IEEE Transactions on Neural Networks
A novel application of a neuro-fuzzy computational technique in event-based rainfall-runoff modeling
Expert Systems with Applications: An International Journal
RFCMAC: A novel reduced localized neuro-fuzzy system approach to knowledge extraction
Expert Systems with Applications: An International Journal
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
Cultural dependency analysis for understanding speech emotion
Expert Systems with Applications: An International Journal
A novel brain-inspired neuro-fuzzy hybrid system for artificial ventilation modeling
Expert Systems with Applications: An International Journal
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There are two important issues in neuro-fuzzy modeling: (1) interpretability---the ability to describe the behavior of the system in an interpretable way---and (2) accuracy---the ability to approximate the outcome of the system accurately. As these two objectives usually exert contradictory requirements on the neuro-fuzzy model, certain compromise has to be undertaken. This letter proposes a novel rule reduction algorithm, namely, Hebb rule reduction, and an iterative tuning process to balance interpretability and accuracy. The Hebb rule reduction algorithm uses Hebbian ordering, which represents the degree of coverage of the samples by the rule, as an importance measure of each rule to merge the membership functions and hence reduces the number of the rules. Similar membership functions (MFs) are merged by a specified similarity measure in an order of Hebbian importance, and the resultant equivalent rules are deleted from the rule base. The rule with a higher Hebbian importance will be retained among a set of rules. The MFs are tuned through the least mean square (LMS) algorithm to reduce the modeling error. The tuning of the MFs and the reduction of the rules proceed iteratively to achieve a balance between interpretability and accuracy. Three published data sets by Nakanishi (Nakanishi, Turksen, & Sugeno, 1993), the Pat synthetic data set (Pal, Mitra, & Mitra, 2003), and the traffic flow density prediction data set are used as benchmarks to demonstrate the effectiveness of the proposed method. Good interpretability, as well as high modeling accuracy, are derivable simultaneously and are suitably benchmarked against other well-established neuro-fuzzy models.