Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Automatic generation of fuzzy rule-based models from data by genetic algorithms
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Information Sciences—Informatics and Computer Science: An International Journal
A cluster validation index for GK cluster analysis based on relative degree of sharing
Information Sciences—Informatics and Computer Science: An International Journal
A study of particle swarm optimization particle trajectories
Information Sciences: an International Journal
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Learning fuzzy inference systems using an adaptive membership function scheme
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic reinforcement learning through symbiotic evolution forfuzzy controller design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Forecasting time series with genetic fuzzy predictor ensemble
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Qualitative modeling of dynamical systems employing continuous-time recurrent fuzzy systems
Fuzzy Sets and Systems
Fuzzy linear regression based on Polynomial Neural Networks
Expert Systems with Applications: An International Journal
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This paper proposes a new approach for automating the structure and parameter learning of fuzzy systems by clustering-aided simplex particle swarm optimization, called CSPSO. Unlike most evolutionary fuzzy systems, where the structure of the fuzzy system is assigned in advance, an on-line fuzzy clustering approach is proposed for system structure learning. This structure learning not only helps determine the number of rules automatically, but also avoids the generation of highly similar fuzzy sets on each input variable. In addition, it improves subsequent parameter learning performance by assigning suitable initial locations of the fuzzy sets on each input variable. Once a new rule is generated, the corresponding parameters are further tuned by the hybrid of the simplex method and particle swarm optimization (PSO). In CSPSO, each fuzzy system corresponds to a particle in PSO, and the idea of the simplex method is incorporated to improve PSO searching performance. To verify the performance of CSPSO, two simulations on feedforward fuzzy systems design are performed. In addition, design of a recurrent fuzzy controller for a practical experiment on water bath temperature control is performed. Comparisons with other design approaches are also made in these examples.