支持向量机及其在地震预报中的应用前景

统计学习理论(SLT)是研究小样本情况下机器学习规律的理论。支持向量机(SVM)基于统计学习理论,可以处理高度非线性分类和回归等问题,不但较好地解决了小样本、过学习、高维数、局部最小等实际难题,而且具有很强的泛化(预测)能力。本文介绍了支持向量机的分类、回归方法,分析了这一方法的特点,讨论了该方法在地震预报中的应用前景。

Support Vector Machines and Its Application Future in Earthquake Predication

Statistical learning theory(SLT) is a small-sample statistics theory.Support vector machine(SVM) is a new machine learning method based on statistical learning theory.It can process the high nonlinear problems with classification and regression.SVM not only can solve some problems,such as small-sample,over-fitting,high-dimension and local minimum,but also has higher generalization(forecasting) ability than that of the artificial neural networks.In this paper,the classification and regression methods of SVM are introduced,the characters of the methods are analyzed,and the application future of SVM in earthquake prediction is discussed also.