Sum normal optimization of fuzzy membership functions
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Training fuzzy systems with the extended Kalman filter
Fuzzy Sets and Systems - Fuzzy systems
Influential Rule Search Scheme (IRSS)-A New Fuzzy Pattern Classifier
IEEE Transactions on Knowledge and Data Engineering
A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method
Information Sciences—Informatics and Computer Science: An International Journal
Design of hierarchical fuzzy model for classification problem using GAs
Computers and Industrial Engineering
A Flexible Content Adaptation System Using a Rule-Based Approach
IEEE Transactions on Knowledge and Data Engineering
Fuzzy classifier design using genetic algorithms
Pattern Recognition
Generating fuzzy rules from training instances for fuzzy classification systems
Expert Systems with Applications: An International Journal
Optimization of rational-powered membership functions using extended Kalman filter
Fuzzy Sets and Systems
Using a hybrid meta-evolutionary rule mining approach as a classification response model
Expert Systems with Applications: An International Journal
A Method to Classify Data by Fuzzy Rule Extraction from Imbalanced Datasets
Proceedings of the 2006 conference on Artificial Intelligence Research and Development
GENERATING AUTOMATIC FUZZY SYSTEM FROM RELATIONAL DATABASE SYSTEM FOR ESTIMATING NULL VALUES
Cybernetics and Systems
Design of hierarchical fuzzy model for classification problem using GAs
Computers and Industrial Engineering
Design of adaptive fuzzy model for classification problem
Engineering Applications of Artificial Intelligence
H∞ estimation for fuzzy membership function optimization
International Journal of Approximate Reasoning
Construction of a neuron-fuzzy classification model based on feature-extraction approach
Expert Systems with Applications: An International Journal
An information theoretic approach to generating fuzzy hypercubes for if-then classifiers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy rule extraction using recombined RecBF for very-imbalanced datasets
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Evolutionary design of fuzzy classifiers using information granules
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Fuzzy clustering-based on aggregate attribute method
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Design of fuzzy rule-based classifier: pruning and learning
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Neurocomputing
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To extract knowledge from a set of numerical data and build up a rule-based system is an important research topic in knowledge acquisition and expert systems. In recent years, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a new fuzzy learning algorithm based on the α-cuts of equivalence relations and the α-cuts of fuzzy sets to construct the membership functions of the input variables and the output variables of fuzzy rules and to induce the fuzzy rules from the numerical training data set. Based on the proposed fuzzy learning algorithm, we also implemented a program on a Pentium PC using the MATLAB development tool to deal with the Iris data classification problem. The experimental results show that the proposed fuzzy learning algorithm has a higher average classification ratio and can generate fewer rules than the existing algorithm