Abstract:  Over-study or under-study phenomenon sometimes happens, since nuclear parameters are chosen inappropriately in regression forecasting. The paper proposes a kind of support vector machine parameters optimization model based on improved genetic algorithm. By combining genetic algorithm with support vector machine algorithm, the model makes use of the principle of evolutionary of genetic algorithm to optimize penalty parameter, nuclear parameter and loss function at the same time, which are of great significance to support vector machine algorithm. Three sets of standard experiment data sets are selected as the test data set, and simulation test results are compared among the improved algorithm, genetic algorithm, particle swarm optimization algorithm and grid search algorithm. Experiment results show that the improved algorithm greatly improves the whole optimization ability of support vector machine algorithm.


Key words: genetic algorithm, support vector machine algorithm, parameters optimization