Support vector machine optimized by particle swarm optimization algorithm for holding nail force forecasting
基于PSO优化的SVM预测应用研究*

In the parameters of support vector machine(SVM) have important effect to SVM performance. The parameters selection is the important research content of the SVM. To this problem, this paper proposed one kind of method to choose the parameters of the SVM by particle swarm optimization algorithm(PSO). The experiment result indicates the SVM regression model optimized by PSO have high forecast accuracy, and PSO is one kind of effective method for SVM parameters choosing.