基于K均值聚类及模糊支持向量机的海洋灾害风险预警方法  

Based on K-means Clustering and Fuzzy Support vector Machine(SVM) Method of Marine Disaster risk early Warning

作　　者：黄东[1] 黄文东[1] 

机构地区：[1]钦州学院数学与计算机科学学院,钦州广西535099

出　　处：《数字技术与应用》2015年第2期86-87,共2页Digital Technology & Application

基　　金：2013年度广西高校科学技术研究项目:<模糊支持向量机及其在海洋灾害风险预测的应用研究>(项目编号:2013YB259);2014年度钦州学院校级科研项目:<无线传感器网络在北部湾海洋生态检测中的应用与研究>(2014XJKY-56C)

摘　　要：我国是世界上海洋灾害最严重、最频发的少数国家之一,本文构建基于K均值聚类及FSVM的海洋灾害风险预警方法,有效解决海洋灾害数据具有不确定性、模糊性及带有扰动信息等问题,从而大大提高海洋灾害预警的准确性,为预测和评价海洋灾害提供更科学的方法,对海洋经济可持续发展有重大意义。实验证明,本文的模型对海洋灾害风险预警具有较高的精确度。China is the Marine disasters in the wodd. It is one of the most serious and frequent countries of the few countries. This paper based on k-means clustering and FSVM Marine disaster risk early warning method, it can effectively solve the Marine disaster data with uncertainty and fuzziness, and the problem of disturbance information and so on. Thus it can gready improve the accuracy of the Marine disaster warning, for prediction and evaluation of Marine disasters to provide a more scientific method, has significant meaning to the Marine economy sustainable development. Experiments show that this model to the Marine disaster risk early warning has higher accuracy.

关 键 词：K均值聚类 FSVM 海洋灾害 风险预警 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]