西北地震学报2012，Vol.34Issue(3)：220-223,233,5.DOI:10.3969/j.issn.1000-0844.2012.03.0220
基于粒子群优化最小二乘向量机的地震预测模型
Earthquake Forecast Model Based on the Partical Swarm Optimization Algorithm Used in LSSVM
摘要
Abstract
In order to overcome the problem of the uncertain parameters in LSSVM model, the PSO-LSSVM prediction model concerning earthquake forecast is developed, which is based on the particle swarm optimization algorithm with abilities of fast convergence and global optimiza-tion. The simulation results show that the proposed method is an effective tool for the prediction of earthquake, and it can effectively enhance the prediction accuracy compared with the way using neural network and support vector machine model.关键词
粒子群优化算法/最小二乘向量机模型/地震预测/参数Key words
Particle swarm optimization ( PSO)/Least squares support vector machine ( LSSVM) model/Earthquake forecast/Parameter分类
天文与地球科学引用本文复制引用
徐松金,龙文..基于粒子群优化最小二乘向量机的地震预测模型[J].西北地震学报,2012,34(3):220-223,233,5.基金项目
国家自然科学基金(61074069) （61074069）
