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Participatory evolution is a learning paradigm recently introduced in the realm of fuzzy system modeling and system optimization. The paradigm benefits from the concept of participatory learning, genetic algorithms and differential evolution. In this paper we address two distinct participatory evolutionary learning algorithms. The first combines participatory learning and the processing steps of differential...
Genetic Fuzzy Systems have been successfully used as a modeling approach for numerous applications. There is an increasing interest on how to construct fuzzy models for different types of complex systems such as highly nonlinear, large-scale, multiobjective, and high-dimensional systems. Current state of the art indicates the use of fast and scalable evolutionary algorithms in complex fuzzy modeling...
This paper introduces a genetic fuzzy system to control short and long term memory of tabu search algorithms. The genetic fuzzy system involves learning of the knowledge base and a rule selection procedure. The aim is to trade-off exploration and exploitation behavior of the search, and to handle high dimensional optimization problems. The genetic fuzzy system approach introduces a high level of autonomy...
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