基于大数据挖掘的自适应准则生成研究

Hongwon Yun, Li Xu, Hao Dou, De-Lie Ming
{"title":"基于大数据挖掘的自适应准则生成研究","authors":"Hongwon Yun, Li Xu, Hao Dou, De-Lie Ming","doi":"10.1109/CGNCC.2016.7828978","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":426650,"journal":{"name":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on adaptation criteria generation based on large data mining\",\"authors\":\"Hongwon Yun, Li Xu, Hao Dou, De-Lie Ming\",\"doi\":\"10.1109/CGNCC.2016.7828978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":426650,\"journal\":{\"name\":\"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CGNCC.2016.7828978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGNCC.2016.7828978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文对基于大量多源遥感数据的自适应分析进行了研究。针对不同任务背景的不同需求,首先研究了如何用计算机语言对数据进行分析。为此,从不同的目标区域地理数据中提取目标区域的特征参数。结合ORACLE数据库引擎,利用数据挖掘技术对目标区域进行适应性评估,并提取相应的适应性准则。在不同目标区域的多源地理信息数据上对训练好的适应准则进行了测试。实验结果表明,所得准则具有一定的符合率和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research on adaptation criteria generation based on large data mining
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Harmonic current detection and suppression based on neural network In-flight correction of alignment errors for SINS/GNSS integrated navigation system Multiple model-based fault diagnosis using unknown input observers Research on adaptive backstepping sliding mode control method for a hex-rotor Unmanned Aerial Vehicle Landing system for AR.Drone 2.0 using onboard camera and ROS
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1