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Prototype selection aims at reducing the scale of datasets to improve prediction accuracy and operation efficiency by removing noisy or redundant patterns via the nearest neighbor classification algorithms. Genetic algorithms have been used recently for prototype selection and showed good performance, however, they have some drawbacks such as the deteriorated running effect, slow convergence for the...
The crossover operator plays an important role in a genetic algorithm, which produces two or more offspring for each pair of parents. With the help of the crossover operator, the genetic algorithm can explore the search space effectively. In this paper, we propose a new crossover operator called elliptical crossover operator, which can explore the search domain effectively. A local search scheme is...
Differential evolution (DE) is a kind of simple but powerful evolutionary optimization algorithm with many successful applications. This paper proposed a multiobjective differential evolutionary algorithm based on opposite operation. Firstly, in the initialization of the algorithm, the opposite points of randomly generated individuals are calculated in order to make the initial population better....
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