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A honey bees mating optimization algorithm for the multigroup credit risk assessment problem

Marinakis Ioannis, Marinaki Magdalini, Zopounidis Konstantinos

Πλήρης Εγγραφή

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Περίληψη

In this paper, a new procedure for solving the Feature Subset Selection problem is presented. This procedure utilizes a honey bees mating optimization algorithm. The Honey Bees Mating Op- timization algorithm simulates the mating process of the queen of the hive. The mating process of the queen begins when the queen flights away from the nest performing the mating flight during which the drones follow the queen and mate with her in the air. The proposed honey bees mating optimization-based classification algorithm is combined with a number of nearest neighbour based classifiers and is tested in a very significant financial classification task, involving the multigroup credit risk assessment problem. The algorithm is compared with a classic genetic algorithm and other metaheuristic algorithms, like Ant Colony Optimization and Particle Swarm Optimization.

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