LS-SVM parameters selection based on genetic algorithm and its application in economic forecasting
基于遗传算法的LS-SVM参数优选及其在经济预测中的应用

It was proposed that genetic algorithm was used to optimize parameters of Least Squares Support Vector Machine (LS-SVM) and LS-SVM was well trained by using population data in an economic system. Then, the well trained LS-SVM was used to forecast population in a city. Finally, LS-SVM and BP network were compared in prediction and the result shows that the genetic algorithm for optimizing parameters of Least Squares Support Vector Machine proposed in this paper is feasible and effective.