本文選題：交通 + 高維數據��； 參考：《重慶交通大學》2015年碩士論文

【摘要】：一直以來,交通數據管理都是一個嚴重的社會問題,由于交通管理部門建立的信息系統(tǒng)大多處于“孤島型”運作,導致交通信息零散、數據之間缺乏必要的內在聯(lián)系等問題的大量存在,從而給交通信息的應用造成了極大的不便。因此,對高維交通數據進行邏輯整合及降解研究對交通數據的管理和應用具有重大的實際意義。本文首先對各種交通檢測數據進行了有關處理,先對各數據進行了時空規(guī)范化處理,具體給出了路網上檢測點位的編碼方法;然后對規(guī)范的交通數據進行有效性判別,對無效的故障數據提出了具體的修復方法;最后對由于檢測設備具有不同檢測精度引起的交通數據沖突予以識別和消減。其次,本文以云計算技術為支撐,借助于分布式存儲的思想,通過對交通數據進行詳細分類,并對各類交通數據進行了維度分析,同時給出了各類交通數據的二維表結構�；诜植际酱鎯Φ睦砟顦嫿艘訦adoop為平臺、以Hbase分布式數據庫為存儲工具的交通數據存儲體系,并對各類交通數據創(chuàng)建了基于IP地址查詢的多級索引,同時對存儲在Hbase中的數據表賦予了相應的IP,在此基礎上實現(xiàn)交通高維數據逐層存儲的目標。這不僅實現(xiàn)了交通高維數據的邏輯整合,也為交通數據的查詢或統(tǒng)計分析提供了方便。針對交通數據的檢索,鑒于交通數據具有明顯的時空特征,首先將所查數據的空間坐標與GIS圖進行映射,得到與該空間位置對應的路網檢測點位,然后對檢測點位上所包含的交通信息進行檢索,通過逐層遍歷,得到存儲該檢測點位上所需信息的IP地址,通過訪問IP地址,得到二維表,最后通過輸入查詢條件,完成對二維表的查詢,得到所查交通數據。論文中的方法基于云平臺,減少了因建立數據中心的巨大花費,同時也能較好的消除系統(tǒng)間的信息孤島現(xiàn)象,使得信息能夠更加高效的互通、共享。不僅為交通信息使用者提供了方便,也為交通管理者提供了決策依據,對交通數據的管理和應用具有一定的實用性和應用價值。
[Abstract]:Traffic data management has always been a serious social problem. Because most of the information systems set up by traffic management departments operate in "isolated islands", traffic information is scattered. There are a lot of problems such as the lack of necessary internal connection between the data, which cause great inconvenience to the application of traffic information. Therefore, the research on logical integration and degradation of high-dimensional traffic data is of great practical significance to the management and application of traffic data. In this paper, we first deal with all kinds of traffic detection data, first, we normalize the data in time and space, and then give the coding method of detecting points on the road network, and then we judge the validity of the standard traffic data. Finally, the traffic data conflict caused by the different detection accuracy of the detection equipment is identified and reduced. Secondly, with the support of cloud computing technology and the idea of distributed storage, the traffic data are classified in detail, and the dimension of traffic data is analyzed, and the two-dimensional structure of traffic data is given. Based on the idea of distributed storage, a traffic data storage system based on Hadoop and Hbase distributed database is constructed, and a multi-level index based on IP address query is created for all kinds of traffic data. At the same time, the corresponding IPs are given to the data table stored in Hbase, and the goal of storing traffic high-dimensional data layer by layer is realized on this basis. This not only realizes the logical integration of high dimensional traffic data, but also provides convenience for the query or statistical analysis of traffic data. For the traffic data retrieval, in view of the obvious space-time characteristics of the traffic data, the spatial coordinates of the data are mapped to the GIS map, and the road network detection points corresponding to the spatial location are obtained. Then the traffic information contained on the detection point is retrieved, and the IP address of the information needed on the detection point is obtained by traversing it layer by layer, and the two-dimensional table is obtained by visiting the IP address, and finally the query condition is input. Complete the query of the two-dimensional table and get the traffic data. The method in this paper is based on cloud platform, which reduces the huge cost of establishing data center, and can eliminate the phenomenon of information isolation between systems, so that the information can be exchanged and shared more efficiently. It not only provides convenience for users of traffic information, but also provides decision basis for traffic managers. It has certain practicability and application value for traffic data management and application.
【學位授予單位】：重慶交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：U491

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本文編號：2071858