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We describe in this paper the architecture of a modular neural network (MNN) for pattern recognition. More recently, the study of modular neural network techniques theory has been receiving significant attention. The design of a recognition system also requires careful attention. The paper aims to use the Ant Colony paradigm to optimize the architecture of this Modular Neural Network for pattern recognition...
In this paper we propose a fuzzy system for parameter adaptation in ant colony optimization (ACO). ACO is a method inspired in the behavior of ant colonies to find food and its objective are discrete optimization problems. We developed various fuzzy systems for parameter adaptation and in this paper a comparison was made between them. The use of a fuzzy system is to control the diversity of the solutions,...
In this paper we describe a new methodology to optimize fuzzy logic controllers using Ant Colony Optimization (ACO); in particular, the fuzzy logic controller for the water tank benchmark problem. The proposed methodology is applied in the optimization of membership function parameters and type of membership functions, using a set of constraints for the construction of the solution matrix of an ACO...
In this paper we describe the optimization of a fuzzy logic controllers using Ant Colony Optimization (ACO); in particular, the fuzzy logic controller for the water tank benchmark problem. The optimization has been done specifically for the type of membership function and membership function parameters.
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