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Genetic algorithms are a practical approach for finding near‐optimal solutions for nondeterministic polynomial‐hard problems. In this work we exploit the parallel processing capability of graphics processing units and Nvidia's CUDA programming platform to accelerate the island model genetic algorithm by modifying the evolutionary operations to fit the hardware architecture and have successfully achieved...
This paper introduces a mechanism to learn optimal classifier combining algorithms for an ensemble system. By using a genetic algorithm approach that focuses on 3 objectives namely the number of correct classified observations, the number of selected features and the number of selected classifiers, optimal solution can be achieved after several interactions of crossover and mutation. We also employ...
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