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基于粗集的遥感影像决策树分类新方法
引用本文:刘峰,潘欣.基于粗集的遥感影像决策树分类新方法[J].长春工程学院学报(自然科学版),2010,11(4):95-97.
作者姓名:刘峰  潘欣
作者单位:中国移动通信集团吉林有限公司,业务支撑中心,长春,130022;长春工程学院,电气与信息工程学院,长春,130012
基金项目:吉林省科技厅青年基金项目
摘    要:土地利用信息是进行土地规划和管理的重要数据,有着重要的经济价值.采用计算机仿真技术对遥感影像进行自动分类是一种获取土地利用数据十分有效的手段.然而遥感影像的不确定、不一致现象易导致过度拟合,增加了分类难度.提出了一种新的基于粗集的决策树用于遥感影像分类.经试验表明该分类方法较CART树、ID3树等算法在分类精度、防止过度拟合方面均有所提高.

关 键 词:粗集  决策树  遥感影像  监督分类

A new method on remote sensing decision tree classification based on rough set
LIU Feng,PAN Xin.A new method on remote sensing decision tree classification based on rough set[J].Journal of Changchun Institute of Technology(Natural Science Edition),2010,11(4):95-97.
Authors:LIU Feng  PAN Xin
Institution:LIU Feng,etc.(Center of Business Support,China Mobile Group Jilin Limited Co.,Changchun,130022,China)
Abstract:Land cover information has been identified as the crucial data for land planning and management,which has important economic value.In order to obtain land cover information,utilizing computer simulation technology to automatically classify the remote sensing images is a very effective measure.However,remote sensing image's uncertainty,inconsistency may lead to the over-fitting phenomenon and increase the difficulty of classification.This paper proposed a new method of remote sensing decision tree based on r...
Keywords:rough set  decision tree  remote sensing  supervised classification  
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