基于支持向量机的渔业资源可持续利用预警方法研究

A way on the early-warning of sustainable use of fisheries resources based on Support Vector Machine

统计学习理论(SLT)是一种专门研究有限样本情况下机器学习规律的理论。支持向量机(Support Vector Machine,SVM)是目前为止该理论最成功的实现。本文在介绍支持向量机(SVM)基本原理的基础上,探讨了基于支持向量机的海洋渔业资源可持续利用预警算法,提出了基于支持向量机的海洋渔业可持续利用预警模型,并以某地区1978-1994年的渔业资源可持续利用状况为例进行了实例分析。本文也同时说明了Libsvm软件在渔业资源可持续利用预警中的应用。

This paper introduces the basic theory of Support Vector Machine （SVM）. A kind of early-warning algorithm of sustainable use of marine fisheries resources based on Support Vector Machine is made. The paper puts forward a model of early-warning of sustainable use of marine fisheries resources based on Support Vector Machine, and it takes the fisheries resources in a area from 1978 to 1994 as an example. This paper has also explained the application of Libsvm software in early-warning of sustainable use of marine fisheries resources.