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
A neuro-fuzzy method to learn fuzzy classification rules from data
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
A new approach of neuro-fuzzy learning algorithm for tuning fuzzy rules
Fuzzy Sets and Systems
Ant Colony Optimization
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy logic for parameter tuning in evolutionary computation and bio-inspired methods
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Application of simulated annealing fuzzy model tuning to umbilical cord acid-base interpretation
IEEE Transactions on Fuzzy Systems
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We describe the use of Ant Colony Optimization (ACO) for the ball and beam control problem, in particular for the problem of tuning a fuzzy controller of the Sugeno type. In our case study the controller has four inputs, each of them with two membership functions; we consider the intersection point for every pair of membership functions as the main parameter and their individual shape as secondary ones in order to achieve the tuning of the fuzzy controller by using an ACO algorithm. Simulation results show that using ACO and coding the problem with just three parameters instead of six, allows us to find an optimal set of membership function parameters for the fuzzy control system with less computational effort needed.