%0 Journal Article
%T Application and improvement of SOM network in remote sensing image classification<br>SOM神经网络改进及在遥感图像分类中的应用*
%A REN Jun-hao
%A JI Pei-qi
%A GENG Yue
%A <br>任军号
%A 吉沛琦
%A 耿跃
%J 计算机应用研究
%D 2011
%I 
%X Contrary to the characteristics and weak point of self-organizing maps neural network, this paper shows a SOM which is improved by genetic algorithm, and improves the method to classifying remote sensing image based on self-organizing mapping network through the input vector, selecting the number of competitive layer neurons and the initializing weight vector. Finally, the method is used to classify an ETM+ satellite remote sensing images of Xi an. It is validated that through the improved self-organizing feature map network based on genetic algorithm, classification of remote sensing image have higher accuracy and efficiency than traditional self-organizing feature map network. The SOM based on genetic algorithm is easy to be achieved, and has practical value.
%K Classification
%K Self-organizing maps
%K Neural network
%K Genetic Algorithm
%K Remote Sensing Image<br>分类
%K 自组织特征映射
%K 神经网络
%K 遗传算法
%K 遥感图像
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=4C48614E2AEF0875635BB1AD7B5AF2DC&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=38B194292C032A66&sid=75AB4EF959CC4ED9&eid=B9196C90508452FE&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9