本文選題：道路網(wǎng) + 同名匹配�。� 參考：《南京師范大學(xué)》2017年碩士論文

【摘要】：道路網(wǎng)空間數(shù)據(jù)是基礎(chǔ)地理數(shù)據(jù)庫(kù)中的重要組成部分,也是導(dǎo)航應(yīng)用、災(zāi)害救援、物流交通等專題數(shù)據(jù)的重要內(nèi)容。因此道路數(shù)據(jù)的現(xiàn)勢(shì)性直接決定這些應(yīng)用能否準(zhǔn)確有效。為促進(jìn)經(jīng)濟(jì)快速發(fā)展,國(guó)家對(duì)基礎(chǔ)建設(shè),特別是各類道路網(wǎng)絡(luò)的建設(shè),投入大量資金,我國(guó)道路網(wǎng)建設(shè)如火如茶,可謂日新月異。道路實(shí)體的變化也促使各類空間數(shù)據(jù)庫(kù)中的道路數(shù)據(jù)也必須及時(shí)更新,只有這樣才能保證空間數(shù)據(jù)庫(kù)的現(xiàn)勢(shì)性。目前,增量更新是數(shù)據(jù)庫(kù)更新的重要方式之一,是保持?jǐn)?shù)據(jù)庫(kù)現(xiàn)勢(shì)性的重要手段。而道路要素的同名匹配和變化檢測(cè)是道路網(wǎng)增量更新過(guò)程中的兩個(gè)關(guān)鍵流程,其中同名要素匹配是實(shí)現(xiàn)增量更新的基礎(chǔ),只有先完成要素匹配才能在此基礎(chǔ)之上檢測(cè)是否發(fā)生變化;而變化檢測(cè)是增量更新的前提,因?yàn)?只有實(shí)現(xiàn)對(duì)變化區(qū)域變化要素的檢測(cè)和提取,才能進(jìn)行增量更新。針對(duì)以上需求,本文引入徑向基函數(shù)網(wǎng)絡(luò)理論和決策樹(shù)理論對(duì)道路要素的同名匹配和道路網(wǎng)變化檢測(cè)與分類進(jìn)行研究,主要成果如下:(1)對(duì)道路網(wǎng)要素的自動(dòng)匹配和變化檢測(cè)兩個(gè)方面的國(guó)內(nèi)外研究現(xiàn)狀進(jìn)行了總結(jié)和分析,在歸納當(dāng)前的研究方法的基礎(chǔ)之上探討了其中存在的一些問(wèn)題。依據(jù)道路網(wǎng)的變化規(guī)律,歸納了道路變化特征因子和道路變化類型,為后面的道路網(wǎng)自動(dòng)匹配和變化檢測(cè)打下了理論基礎(chǔ)。(2)提出了基于徑向基函數(shù)網(wǎng)絡(luò)的多特征因子路網(wǎng)匹配方法。本文綜合利用道路網(wǎng)中路段的長(zhǎng)度、距離、形狀、方向等幾何特征的相似度和結(jié)點(diǎn)的拓?fù)涮卣鞯南嗨贫鹊?個(gè)空間特征相似度指標(biāo)對(duì)多源道路網(wǎng)進(jìn)行相似度判斷。為解決各個(gè)相似度指標(biāo)在匹配中的權(quán)重分配問(wèn)題,引入徑向基函數(shù)網(wǎng)絡(luò)理論,并對(duì)經(jīng)典徑向基函數(shù)進(jìn)行改進(jìn),改進(jìn)后的徑向基函數(shù)網(wǎng)絡(luò)顧及了不同路網(wǎng)相似度指標(biāo)在路網(wǎng)匹配中所起作用不同這一特點(diǎn),使徑向基函數(shù)具有各向異性特征。在神經(jīng)網(wǎng)絡(luò)輸出層引入sigmoid函數(shù),對(duì)匹配結(jié)果值作歸一化處理,從而實(shí)現(xiàn)道路網(wǎng)的可靠匹配。通過(guò)與常用的BP神經(jīng)網(wǎng)絡(luò)在道路網(wǎng)匹配中的效果進(jìn)行比較,實(shí)驗(yàn)證明徑向基函數(shù)網(wǎng)絡(luò)在樣本訓(xùn)練和路網(wǎng)匹配時(shí)效率更高,匹配準(zhǔn)確率也更高。(3)提出了基于決策樹(shù)的道路網(wǎng)變化檢測(cè)與分類方法。設(shè)定路長(zhǎng)、路型、方向、結(jié)點(diǎn)度以及屬性等5個(gè)道路變化特征因子作為決策樹(shù)的特征,改進(jìn)傳統(tǒng)決策樹(shù)生成過(guò)程中基于信息增益選擇特征的方法,利用道路變化特征影響力算法快速計(jì)算樣本數(shù)據(jù)的道路變化特征的影響力值,基于特征影響力值排序來(lái)選擇決策樹(shù)特征,生成道路變化分類的決策樹(shù),進(jìn)而完成道路網(wǎng)變化的檢測(cè)和變化類型分類。(4)在本文理論研究成果的基礎(chǔ)之上,設(shè)計(jì)并開(kāi)發(fā)了道路網(wǎng)變化檢測(cè)與分類原型系統(tǒng)。該系統(tǒng)可以實(shí)現(xiàn)道路網(wǎng)數(shù)據(jù)的管理、簡(jiǎn)單的數(shù)據(jù)預(yù)處理、道路網(wǎng)同名匹配、道路網(wǎng)變化檢測(cè)以及道路數(shù)據(jù)的變化信息查詢、屬性查詢和空間查詢等功能。
[Abstract]:The road network spatial data is an important part of the basic geographic database, and it is also an important part of the special data of navigation applications, disaster relief, logistics and transportation. Therefore, the potential of road data directly determines whether these applications can be accurate and effective. In order to promote the rapid economic development, the national infrastructure, especially the various road networks, can be used to promote the rapid economic development. Building and investing a lot of money, the construction of road network in China is like tea, which is changing rapidly. The change of road entity also prompt the road data in all kinds of spatial databases to be updated in time. Only in this way can we guarantee the potential of spatial database. At present, incremental updating is one of the important ways to update the database, and it is to maintain the database. The same name matching and change detection of road elements are the two key processes in the process of incremental updating of the road network, in which the matching of the same name elements is the basis for incremental updating. Only by completing the matching of elements before the detection is based on this, the change detection is the prerequisite for incremental updating. In order to carry out incremental updating only by detecting and extracting the factors of changing regional changes, this paper introduces radial basis function network theory and decision tree theory to study the homonym matching of road elements and the detection and classification of road network changes. The main achievements are as follows: (1) automatic matching of road network elements and the main results are as follows. The current research situation at home and abroad in two aspects of change detection is summarized and analyzed. On the basis of summarizing the current research methods, some problems are discussed. According to the change law of road network, the characteristic factors of road change and the type of road change are summed up, and the automatic matching and change detection of the road network are laid down. The theoretical basis. (2) a multi characteristic factor road network matching method based on radial basis function network is proposed. In this paper, the similarity degree between the length, distance, shape, direction and other geometric features such as the length, distance, shape, direction and other geometric features of the road network is used to judge the similarity degree of the multi source road network. In order to solve the weight allocation problem in the matching, the radial basis function network theory is introduced, and the classical radial basis function is improved. The improved radial basis function network takes into account the different functions of the similarity index of different road networks in the road network matching, and makes the radial basis function have the anisotropic characteristics. The sigmoid function is introduced through the network output layer, and the matching results are normalized to achieve a reliable match of the road network. By comparing the effects of the common BP neural network in the road network matching, the experimental results show that the radial basis function network is more efficient and more accurate in the sample training and road network matching. (3) The method of road network change detection and classification based on decision tree is proposed. 5 road change features are set as the characteristics of the decision tree, which are the path length, the road pattern, the direction, the node degree and the attribute, and the method based on the information gain selection feature is improved in the traditional decision tree generation process. The method is used to quickly calculate the sample with the road change feature influence algorithm. The influence value of the road change characteristics of the data, based on the characteristic influence value sorting to select the decision tree characteristics, generate the decision tree of the road change classification, and then complete the road network change detection and the change type classification. (4) on the basis of the theoretical research results of this paper, the road network change detection and classification prototype system is set up and developed. The system can realize the management of road network data, simple data preprocessing, road network homonym matching, road network change detection, road data change information query, attribute query and spatial query.

【學(xué)位授予單位】：南京師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P208

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本文編號(hào)：1830930