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A self-generating fuzzy system with ant and particle swarm cooperative optimization
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IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Modified PSO Structure Resulting in High Exploration Ability With Convergence Guaranteed
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Combination of online clustering and Q-value based GA for reinforcement fuzzy system design
IEEE Transactions on Fuzzy Systems
Genetic algorithm-based optimal fuzzy controller design in the linguistic space
IEEE Transactions on Fuzzy Systems
Incremental Evolutionary Design of TSK Fuzzy Controllers
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
IEEE Transactions on Fuzzy Systems
Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization
Expert Systems with Applications: An International Journal
Modeling with discrete-time recurrent fuzzy systems via mixed-integer optimization
Fuzzy Sets and Systems
Optimization of fuzzy systems using group-based evolutionary algorithm
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Differential evolution with local information for neuro-fuzzy systems optimisation
Knowledge-Based Systems
International Journal of Intelligent Information and Database Systems
International Journal of Intelligent Information and Database Systems
Computers in Biology and Medicine
Evaluating the performance of a Bayesian Artificial Immune System for designing fuzzy rule bases
International Journal of Hybrid Intelligent Systems
International Journal of Hybrid Intelligent Systems
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This paper proposes the design of fuzzy-rule-based systems using continuous ant-colony optimization (RCACO). RCACO determines the number of fuzzy rules and optimizes all the free parameters in each fuzzy rule. It uses an online-rule-generation method to determine the number of rules and identify suitable initial parameters for the rules and then optimizes all the free parameters using continuous ant-colony optimization (ACO). In contrast to traditional ACO, which optimizes in the discrete domain, the RCACO optimizes parameters in the continuous domain and can achieve greater learning accuracy. In RCACO, the path of an ant is regarded as a combination of antecedent and consequent parameters from all the rules. A new path-selection method based on pheromone levels is proposed for initial-solution construction. The solution is modified by sampling from a Gaussian probabilitydensity function and is then refined using the group best solution. Simulations on fuzzy control of three nonlinear plants are conducted to verify RCACO performance. Comparisons with other swarm intelligence and genetic algorithms demonstrate the advantages of RCACO.