Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Evolving Compact and Interpretable Takagi–Sugeno Fuzzy Models With a New Encoding Scheme
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
GA-fuzzy modeling and classification: complexity and performance
IEEE Transactions on Fuzzy Systems
The WM method completed: a flexible fuzzy system approach to data mining
IEEE Transactions on Fuzzy Systems
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Fuzzy systems are currently used in many kinds of applications, such as control, for their effectiveness and efficiency. However, these characteristics depend primarily on the model yield by human experts, which may or may not be optimized for the problem at hand. Particle swarm optimization (PSO) is a technique used in complex problems, including multi-objective problems. In this paper, we propose an algorithm that can generate fuzzy systems automatically for different kinds of problems by simply providing the objective function and the problem variables. This automatic generation is performed using PSO. To be able to do so and in order to avoid dealing with inconsistent fuzzy systems, we used some known techniques, such as the WM method, to help in developing meaningful rules and clustering concepts to generate membership functions. Tests using the sigmoid 3D curve have been carried out and the obtained results are presented.