Amira Hamdi

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This paper describes a novel bio-inspired metaheuristic named ASClass for data clustering problem. The particular principles used for the design of this strategy are inspired by the foraging behavior observed in ant colony. In this technique, an ant colony optimization algorithm is used to search a closed tour of minimal length connecting n objects in(More)
This paper provides a new method for arranging data sets into clusters. The proposed model, called FlyAntClass, starts from the ants collective sorting behavior and overwrites it with additional behaviors inspired from birds and spiders: in this context, birds' moving behavior is used to control next relative positions for a moving ant; and spiders' homing(More)
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