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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/30407

Title: 主要成份分析法於軌跡探勘之應用研究
Trajectory Mining with Principal Components Analysis
Authors: Ming-Hsuan Lu
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: GPS;軌跡探勘;主要成份分析法;平均位移演算法
GPS;trajectory minging;principal component analysis;mean shift algorithm
Date: 2011
Issue Date: 2011-11-25T07:43:47Z
Abstract: 隨著科技的發展,全球各地隨時都在快速累積著因各種應用需求而取得的 GPS (Global Positioning System) 軌跡資料,而從這些資料可挖掘出的資訊也因此成了近年的熱門研究主題之一。然而,GPS資料接收傳送的過程中往往因各種因素造成資料失真,影響軌跡資料的參考價值,本論文以主要成份分析法結合平均位移演算法設計出一個搜尋時不必用到軌跡識別與時間資料,僅需軌跡點的座標即可追蹤出移動物體原始航跡並保留航跡特徵的軌跡探勘方式,實作過程中再以自行模擬產生的軌跡資料對追蹤時相關參數的設定進行探討,找出同時符合直線以及曲線的參數設定準則。
With the development of technology, the GPS (Global Positioning System) tracks information is rapidly collected to satisfy the application needs for users at all time around the world. The trajectory information from database has becomes one of the popular research topics in recent years. However, the distortions of GPS track information may be caused in data logging process and eventually generate non-valuable track data. The aim of this study is to demonstrate how to combine the average principal component analysis with mean shift algorithm for an enhanced searching way. It further allows the professional to easily receive the initial trajectory information of moving objects by tracking their coordinate and to retain the track features and the trajectory of exploration mode. In addition, this report will research into how parameter setting affects the result of trajectory information at self-generated simulation; meanwhile producing a guideline to meet the parameter setting of straight-line and curve in the actual implementation.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M98670027
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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