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研究生:孫瑞廷
研究生(外文):Rui-Ting Sun
論文名稱:利用雲端計算之磁性入侵物偵測系統
論文名稱(外文):A magnetic intruder detection system based on cloud computing
指導教授:李錫智李錫智引用關係
指導教授(外文):Shie-Jue Lee
學位類別:碩士
校院名稱:國立中山大學
系所名稱:電機工程學系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:101
語文別:中文
論文頁數:65
中文關鍵詞:遠端監控機器學習人工智慧雲端運算
外文關鍵詞:machine learningartificial intelligencecloud computing
相關次數:
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  • 下載下載:18
  • 收藏至我的研究室書目清單書目收藏:0
台灣四面環海,海洋運輸因此成為台灣重要的經濟命脈。有鑑於此,本文研究一透過雲端運算與分散式儲存的系統,可用於收集散佈於海面上的監測感
應器所提供的大量資料進行運算、分析,進而判斷是否有會造成磁場異常擾動的帶磁性入侵物出現與其所在方位與運動方向的辨識。
我們利用Apache基金會所提供的Hadoop平台進行可分散處理的K-Means分群運算、收集搭載磁場感應器與DGPS定位裝置的海面感應器節點所獲得的資料,並判斷入侵物的有無與可能的移動方向,並將此結果回傳到遠端的監控終端。除了K-Means分群演算法相當適合處理磁場異常的偵測以外、本系統也透過Hadoop平台獲得優秀的可靠性與效率。
Taiwan is surrounded by ocean, thus the ocean transportation has become the necessary support of Taiwan''s economy. Due to this fact, this research provides a system based on cloud computing and distributed storage which is applied to compute large amount of data provided by many sensors on the sea in order to diagnose the existence of possible magnetized invaders.
We use Hadoop platform from Apache Foundation to proceed distributable K-means clustering computation to process the data collected f
rom many sensor nodes containing DGPS and magnetic sensors. With these data, it is possible to diagnose the existence and the moving direction of the possible invader. And the result can be return to remote monitoring terminal. Not only K-means can detect the irregularity of any axis of the magnetic field well, but also this system obtain good reliability and performance by Hadoop platform.
The goal system can detect the irregularity of any axis of the magnetic field well enough by deploying K-Means clustering and obtain good reliability and performance by Hadoop platform.
致謝 iv
中文摘要 v
Abstract vi
第一章 緒論 1
1.1 研究動機 1
1.2 問題定義 3
1.3 論文架構 4
第二章 文獻探討 5
2.1 磁場量測相關 5
2.2 機器學習相關 7
2.3 雲端運算相關 8
第三章 研究方法 12
3.1 系統概觀 12
3.2 訓練流程 13
3.3 訓練方法 14
第四章 實驗範例與結果 20
4.1 實驗器材與環境 20
4.2 磁場偵測入侵物相對位置方向實驗數據 26
4.3 磁場入侵物運動方向實驗數據 36
4.4 磁場入侵物實驗數據歸納 46
4.5 K-means實作效能比較 47
第五章 結論與未來展望 50
5.1 結論 50
5.2 未來展望 50
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