| 查看: 277 | 回复: 1 | ||
[求助]
请帮忙查一下是否检索
|
|
想知道是否被检索，劳驾虫友查阅：The Spatial Classification Algorithm of K-Nearest Neighbor Based on Spatial Predicate Ma Yu, Gao Yuling, Song Shaoyun |
回复此楼» 猜你喜欢
面上可以超过30页吧？
已经有13人回复
-
网上报道青年教师午睡中猝死、熬夜猝死的越来越多，主要哪些原因引起的？
已经有10人回复
-
为什么中国大学工科教授们水了那么多所谓的顶会顶刊，但还是做不出宇树机器人？
已经有13人回复
-
什么是人一生最重要的？
已经有8人回复
-
版面费该交吗
已经有17人回复
-
体制内长辈说体制内绝大部分一辈子在底层，如同你们一样大部分普通教师忙且收入低
已经有19人回复
-
【博士招生】太原理工大学2026化工博士
已经有8人回复
-
280求调剂
已经有4人回复
» 本主题相关价值贴推荐，对您同样有帮助:
- 帮忙查一下是否检索
已经有3人回复
- 帮忙下载doc88文章，谢谢
已经有2人回复
- 请帮忙查一下文章是否被检索，谢谢！
已经有3人回复
- 哪位帮我查一下这篇文章现在能被web of science出sci检索报告吗？（金币为谢）
已经有15人回复
- 请大家帮忙查一下，下面的3篇会议论文，是否被ISTP检索，请给出检索号，奖励20金币！
已经有11人回复
- 请哪位大侠帮忙查一篇文章是否被ISTP检索
已经有5人回复
【答案】应助回帖
|
Accession number: 20132916505588 Title: The spatial classification algorithm of K-nearest neighbor based on spatial predicate Authors: Ma, Yu1 ; Gao, Yu Ling2 ; Song, Shao Yun1 Author affiliation: 1 School of Information Technology and Engineering, Yuxi Normal University, Yuxi, Yunnan, China 2 School of Foreign Languages, Yuxi Normal University, Yuxi, Yunnan, China Source title: Advanced Materials Research Abbreviated source title: Adv. Mater. Res. Volume: 706-708 Monograph title: Mechatronics and Intelligent Materials III Issue date: 2013 Publication year: 2013 Pages: 1928-1931 Language: English ISSN: 10226680 ISBN-13: 9783037857106 Document type: Conference article (CA) Conference name: 2013 3rd International Conference on Mechatronics and Intelligent Materials, MIM 2013 Conference date: May 18, 2013 - May 19, 2013 Conference location: XiShuangBanNa, China Conference code: 97695 Sponsor: Hong Kong Control Engin. and Inform.; Science Research Assoc. (CEIS); Internat. Frontiers of science and; technol. Research Assoc. (IFST); Integrated Research Center for Green Living Techniques; National Chin-Yi University of Technology Publisher: Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland Abstract: Traditional k-Nearest Neighbor Algorithm (short for KNN) is usually used in the spatial classification; however, the problem of low-speed searching exists in this method. In order to avoid this kind of disadvantage, this paper puts forward a new spatial classification algorithm of K-nearest neighbor based on spatial predicate. This method searches the object set which is similar to the test object in spatial concept and uses spatial predicate to help search the object set, which narrows the searching range and reduces the operating time of KNN algorithm. © (2013) Trans Tech Publications, Switzerland. Number of references: 7 Main heading: Learning algorithms Controlled terms: Intelligent materials - Pattern recognition Uncontrolled terms: K nearest neighbor algorithm - K-nearest neighbors - k-NN algorithm - Operating time - Spatial classification - Spatial concepts - Spatial predicates - Test object Classification code: 415 Metals, Plastics, Wood and Other Structural Materials - 716 Telecommunication; Radar, Radio and Television - 723 Computer Software, Data Handling and Applications DOI: 10.4028/www.scientific.net/AMR.706-708.1928 Database: Compendex Compilation and indexing terms, © 2012 Elsevier Inc. |
2楼2013-07-28 09:05:42