Research on Adaptation Criteria Generation based on Large Data Mining

被引:0
|
作者
Yun Hong-quan [1 ]
Xu Li [1 ]
Dou Hao [2 ]
Ming De-lie [2 ]
机构
[1] Beijing Aerosp Automat Control Inst, Natl Key Lab Sci & Technol Aerosp Intelligence Co, Beijing 100854, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Automat, State Key Lab Multispectral Informat Proc Technol, Wuhan 430074, Peoples R China
来源
2016 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC) | 2016年
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper performs research on adaptation analysis based on large amount of multi-source remote sensing data. In view of different demands from different task background, the research is firstly focused on how to analyze the data in computer language. To achieve this, the feature parameters of target areas are extracted from different target area geographic data. In combination of ORACLE database engine, data mining technology is used to carry out the target area adaptation assessment, and extract corresponding adaptation criteria. We test the trained adaptation criteria on multi-source geographic information data of different target areas. Experimental results show that the resulting criterion has certain coincidence rate and robustness.
引用
收藏
页码:1311 / 1316
页数:6
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