首页 | 本学科首页   官方微博 | 高级检索  
     

森林类型遥感识别人工自组织神经树模型初探
引用本文:全志杰 褚泓阳. 森林类型遥感识别人工自组织神经树模型初探[J]. 西北林学院学报, 1997, 12(1): 66-69
作者姓名:全志杰 褚泓阳
作者单位:西北林学院林学系
基金项目:国家“八五”科技攻关项目
摘    要:运用森林类型遥感目视识别的70个样本,训练人工自组织神经树模型,然后对10个“未知”样本进行预测。结果表明,该模型的识别、容错能力较强,综合了遥感图像专家目视判读与计算机自动识别的优点,使判读过程更加精确和简练,而且省工、省时、省经费。开拓了遥感识别地物的新途径

关 键 词:森林类型;遥感;人工自组织神经树模型

A Study on Remote Sensing Recognition of Artificial Self-organization Neural Tree Model of Forest Type
Quan Zhijie ) Chu Hongyang ) Wang Lihong ) Mao Xiaoli ) Li Yuanke ). A Study on Remote Sensing Recognition of Artificial Self-organization Neural Tree Model of Forest Type[J]. Journal of Northwest Forestry University, 1997, 12(1): 66-69
Authors:Quan Zhijie ) Chu Hongyang ) Wang Lihong ) Mao Xiaoli ) Li Yuanke )
Affiliation:Quan Zhijie 1) Chu Hongyang 2) Wang Lihong 3) Mao Xiaoli 1) Li Yuanke 1)
Abstract:A model of artificial self-organizing neural tree was trained by 70 sample books of forest type recognized by visual remote sensing recognization. The trained model was then evaluated by the recognition of 10 unknown samples. The results showed the abilities of recognition and fault tolerance of the model were strong. It combines the advantages of visual interpretation of remote sensing photoes with automatic computer recognition, which makes the recognition not only more accurate and concise, but also time, money and labour saving. It opens up a new way for remote sensing recognition of object.
Keywords:forest type  remote sensing  artificial self-organizing neural tree model  
本文献已被 CNKI 维普 等数据库收录!
点击此处可从《西北林学院学报》浏览原始摘要信息
点击此处可从《西北林学院学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号