Algorithms for clustering data
Algorithms for clustering data
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Identification of functional fuzzy models using multidimensional reference fuzzy sets
Fuzzy Sets and Systems
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Constructing a fuzzy controller from data
Fuzzy Sets and Systems - Special issue on methods for data analysis in classificatin and control
A simple but powerful heuristic method for generating fuzzy rules from numerical data
Fuzzy Sets and Systems
A Robust Competitive Clustering Algorithm With Applications in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
About the use of fuzzy clustering techniques for fuzzy model identification
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Essentials of Fuzzy Modeling and Control
Essentials of Fuzzy Modeling and Control
Comparison of clustering algorithms for analog modulation classification
Expert Systems with Applications: An International Journal
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
Fuzzy function approximation with ellipsoidal rules
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
A transformed input-domain approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Robust TSK fuzzy modeling for function approximation with outliers
IEEE Transactions on Fuzzy Systems
Artificial Intelligence in Medicine
Applying particle swarm optimization algorithm to roundness measurement
Expert Systems with Applications: An International Journal
Active contour model via multi-population particle swarm optimization
Expert Systems with Applications: An International Journal
Application of Radial Basis Function Neural Network for Sales Forecasting
CAR '09 Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics
A fuzzy modeling method via Enhanced Objective Cluster Analysis for designing TSK model
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Linguistic fuzzy model identification based on PSO with different length of particles
Applied Soft Computing
Cost estimation of plastic injection molding parts through integration of PSO and BP neural network
Expert Systems with Applications: An International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
| Hi-index | 12.06 |
This paper introduces a novel hybrid algorithm for function approximation. The proposed algorithm consists of a hybrid approach to develop Takagi and Sugeno's fuzzy model for function approximation. In this paper, a coarse tuning based on Takagi and Sugeno's fuzzy model is applied to identify the fuzzy structure, and also a fuzzy cluster validity index is utilized to determine the optimal number of clusters. To obtain a more precision model, genetic algorithm (GA) and particle swarm optimization (PSO) are performed to conduct fine-tuning for the obtained parameter set of the premise parts and consequent parts in the aforementioned fuzzy model. The proposed algorithm is successfully applied to three tested examples. Compared with other existing approaches in the literature, the proposed algorithm is very useful for modeling function approximation.