本文選題：協(xié)同綜合 + 匯水區(qū)域��； 參考：《南京師范大學(xué)》2014年碩士論文

【摘要】：地理信息的自動綜合是數(shù)字環(huán)境下地圖學(xué)與GIS的國際性難題之一。傳統(tǒng)基于數(shù)學(xué)模型的綜合方法由于無法描述地圖綜合中大量的模糊性問題,所以無法全面解決地圖自動綜合問題。多要素協(xié)同綜合思想的提出,在一定程度上減少了綜合后要素間的沖突問題,但現(xiàn)有關(guān)于多要素協(xié)同綜合的研究,多集中在某些特定區(qū)域類型或分布特征的地區(qū),尚無較為全面的多要素協(xié)同綜合解決方案。自然環(huán)境下的等高線與河網(wǎng)在地理成因上相輔相成,具有天然的耦合關(guān)系,因而成為協(xié)同綜合研究的首選。 隨著計算機(jī)、人工智能技術(shù)的發(fā)展,Agent所具有的自我工作和思維能力,能夠模仿地圖綜合專家的思維過程,提高地圖綜合的自動化水平。但由于現(xiàn)有等高線與河網(wǎng)地圖綜合知識的“深度”和“廣度”不夠,制約了其智能化綜合的發(fā)展。將匯水區(qū)域納入到協(xié)同綜合范疇之中,將有利于進(jìn)一步統(tǒng)一等高線與河網(wǎng)的結(jié)構(gòu)化綜合。并且匯水區(qū)域內(nèi)部等高線與河流空間關(guān)系較為簡單,能有效的降低沖突問題的復(fù)雜性。 為了實現(xiàn)本文提出的智能協(xié)同綜合方法,首先總結(jié)了現(xiàn)有等高線與河網(wǎng)的協(xié)同綜合知識,使用匯水區(qū)域邊界作為等高線與河網(wǎng)協(xié)同綜合的約束條件,將匯水區(qū)域作為協(xié)同綜合的最小單元,針對不同類型匯水區(qū)域設(shè)計了不同的綜合方法。在此基礎(chǔ)上分析了匯水區(qū)域約束下等高線與河網(wǎng)智能協(xié)同綜合的Agent分類,給出了各個綜合Agent的屬性與行為。然后對本文提出的匯水區(qū)域約束的協(xié)同綜合方法進(jìn)行了形式化表達(dá),提出了匯水區(qū)域約束下等高線與河網(wǎng)的智能協(xié)同綜合模型。最后基于JADE開發(fā)了地圖多要素智能協(xié)同綜合系統(tǒng)MAPGen,并做了試驗驗證。通過分析實驗結(jié)果,證明了本文提出的智能協(xié)同綜合方法,能夠很好的保持多尺度綜合后等高線與河網(wǎng)的各種空間與語義關(guān)系,有效避免了綜合后地圖目標(biāo)之間的沖突。
[Abstract]:Automatic synthesis of geographic information is one of the international problems of cartography and GIS in digital environment. Because the traditional mathematical model based synthesis method can not describe a large number of fuzzy problems in map synthesis, it is unable to solve the problem of map automatic synthesis in an all-round way. The idea of multi-factor synergy synthesis reduces the conflict problem among the elements after synthesis to a certain extent. However, the existing research on multi-factor synergy synthesis is mainly focused on the areas with certain regional types or distribution characteristics. There is no comprehensive multi-factor cooperative solution. The contour line and river network in the natural environment complement each other in geographical origin and have natural coupling relationship, so they become the first choice of collaborative synthesis research. With the development of computer and artificial intelligence technology, Agent has the ability of self-work and thinking, which can imitate the thinking process of map synthesis experts and improve the automation level of map synthesis. However, the existing contour map and river network map synthesis knowledge "depth" and "breadth" is not enough, which restricts the development of its intelligent synthesis. Bringing the catchment area into the category of synergetic synthesis will help to further unify the structural synthesis of contour line and river network. And the relationship between the contour and the river space is relatively simple, which can effectively reduce the complexity of the conflict problem. In order to realize the intelligent cooperative synthesis method proposed in this paper, firstly, the existing knowledge of collaborative synthesis between contour lines and river networks is summarized, and the boundary of catchment area is used as the constraint condition for the collaborative synthesis of contour lines and river networks. Taking the catchment area as the minimum unit of collaborative synthesis, different synthesis methods are designed for different types of catchment areas. On this basis, the Agent classification of intelligent cooperative synthesis of contour line and river network under the constraint of catchment area is analyzed, and the attributes and behaviors of each synthetic Agent are given. Then, the collaborative synthesis method of catchment region constraints proposed in this paper is formalized, and the intelligent cooperative synthesis model of contour line and river network under catchment area constraint is proposed. Finally, the map multi-element intelligent cooperative synthesis system MAPGenbased on JADE is developed and tested. By analyzing the experimental results, it is proved that the intelligent cooperative synthesis method proposed in this paper can maintain the spatial and semantic relationships between contour lines and river networks after multi-scale synthesis, and effectively avoid the conflict between map targets after synthesis.
【學(xué)位授予單位】：南京師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P208

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本文編號：1985576