本文關鍵詞： 空間數據庫 自動泛化 相似變換 模糊空間關系多維縮放地圖 隸屬函數 利用地理信息系統(tǒng) 模糊集理論 模糊邏輯　出處：《北京理工大學》2015年博士論文　論文類型：學位論文

【摘要】：與離散化表示和模糊空間目標相結合的自動控制在多維矢量地圖空間目標上已經出現了矛盾和不一致性。許多處理空間對象的空間數據庫,由于其本質上的不確定性和模糊的本質,而不能充分地用確定性、明確的空間概念描述。地理信息系統(tǒng)和空間數據庫系統(tǒng)目前無法精確地應對這種空間對象。是建設空間數據庫的必要工具。建設空間數據庫是空間數據基礎設施的關鍵,它為社會中像經濟、國防、教育、交通、PD、環(huán)境保護、科研、電信等眾多領域提供了地理空間定位基地。然而,這仍然是一個理想,因為特征空間中的對象映射的概括是并不是沒有參數的,因此需要人為的干擾。其中一個重要的原因是,自動泛化空間相似變換在多維尺度矢量地圖空間是模糊性的。并且,沒有發(fā)現一種理論支持這種類型的轉換。本文側重于開發(fā)基于多維尺度矢量地圖空間的模糊空間相似關系的理論,針對提出的定義、模式和方法,可以在多維尺度矢量地圖空間中選擇自動參數泛化算法。系統(tǒng)的回顧現有的成果,包括相似性的定義,評估各領域相似的特點,分類系統(tǒng)解決相似的特點和從數學、心理學、信息科學和地理領域測量工具的相似性關系,以及基于大量的柵格模型來衡量圖像之間的相似度。本文取得了如下創(chuàng)新性的貢獻。首先實現了模糊集理論的效用和模糊邏輯的相似變換用于多維尺度矢量地圖的發(fā)展空間推廣過程中,首次在文學理論開發(fā)了模糊空間相似關系的理論的實用程序。在自動綜合的上下文中,沒有報道過這項工作。第二,在地理空間和多維尺度向量圖上,模糊空間相似關系是基于模糊集理論范式,而不是脆的空間對象的集合理論的范式,這增強了建�？臻g對象的能力。第三是提出了基于模糊關系的模糊空間相似關系自動綜合的特點和模糊邏輯,以加強在地理空間和多維尺度矢量地圖理論的邏輯關系。第四是模糊因素,其識別和模糊性在空間對象的相似變換地理空間和多維尺度向量地圖空間中的貢獻。第五是提出模糊化程序,以獲取隸屬函數的模糊度的全貌,使我們在參數選擇的空間對象的相似變換中能有一個非常清楚和最優(yōu)決策的完整畫面。雖然這項研究側重于自動泛化的模糊空間相似關系,特別是在地形圖,但這種理論的應用超過了GIS的領域。我們稱之為空間對象的空間數據處理的科學與工程的任何分支將受益于模糊空間相似性關系。它能被利用于如空間邏輯,空間推理領域,從而最終將其利益擴大到測繪工程、醫(yī)學、健康、基因工程、計算機輔助設計、計算機輔助制造和機器人技術領域等這些有助于國家經濟發(fā)展的領域。
[Abstract]:The automatic control combined with discrete representation and fuzzy spatial object has already appeared contradiction and inconsistency on multi-dimensional vector map spatial target. Many spatial databases dealing with spatial objects. Because of its inherent uncertainty and fuzzy nature, it can not fully use certainty. A clear description of spatial concepts. Geographic information systems and spatial database systems are currently unable to respond precisely to such spatial objects. They are essential tools for the construction of spatial databases, which are the spatial data infrastructure. The key. It provides geo-spatial positioning bases in many areas of society, such as economy, national defense, education, transportation PDs, environmental protection, scientific research, telecommunications, etc. However, this is still an ideal. Because the generalization of object mapping in a feature space is not parameterless, it requires human interference. One of the important reasons is that. Automatic generalization spatial similarity transformation is fuzzy in multi-dimensional vector map space. No theory has been found to support this type of transformation. This paper focuses on the development of fuzzy spatial similarity relations based on multidimensional scale vector map space, aiming at the proposed definitions, patterns and methods. Automatic parameter generalization algorithm can be selected in multidimensional scale vector map space. The system reviews the existing results including the definition of similarity and evaluates the characteristics of similarity in various fields. The classification system addresses the similarity between similar features and measurement tools from mathematics, psychology, information science and geography. And based on a large number of raster models to measure the similarity between images. This paper has made the following innovative contributions. Firstly, the utility of fuzzy set theory and the similarity transformation of fuzzy logic are realized for multidimensional scale vector map. In the process of developing and popularizing. For the first time, a practical program for the theory of similarity in fuzzy space has been developed in literary theory. This work has not been reported in the context of automatic synthesis. Secondly, in geographical space and multidimensional scale vector graph. The similarity relationship in fuzzy space is based on the paradigm of fuzzy set theory, not the paradigm of set theory of brittle spatial objects. This enhances the ability of modeling spatial objects. Thirdly, the characteristics and fuzzy logic of automatic synthesis of fuzzy spatial similarity relations based on fuzzy relations are proposed. In order to strengthen the logical relationship of vector map theory in geographic space and multidimensional scale. 4th is the fuzzy factor. The contribution of its recognition and fuzziness to the similar transformation of spatial objects in geographic space and multidimensional scale vector map space. 5th is a fuzzification program proposed to obtain a complete picture of the fuzziness of membership function. It enables us to have a very clear and complete picture of optimal decision in the similarity transformation of spatial objects with parameter selection, although this study focuses on the automatic generalization of fuzzy spatial similarity relations, especially in topographic maps. But the application of this theory extends beyond the domain of GIS. Any branch of science and engineering that we call spatial data processing will benefit from fuzzy spatial similarity relations. It can be used for example spatial logic. . Spatial reasoning will ultimately extend its benefits to mapping engineering, medicine, health, genetic engineering, and computer-aided design. Areas such as computer-aided manufacturing and robotics are areas that contribute to the country's economic development.
【學位授予單位】：北京理工大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：P208

【參考文獻】

相關期刊論文 前4條

1 ;Fundamental Theories of Spatial Similarity Relations in Multi-scale Map Spaces[J];Chinese Geographical Science;2010年01期

2 徐澤水;;區(qū)間直覺模糊信息的集成方法及其在決策中的應用[J];控制與決策;2007年02期

3 李家莼;從圖形相似到事物相似[J];四川工業(yè)學院學報;2000年02期

4 梁俊雄;相似關系的基本概念及其弱等價性質[J];系統(tǒng)工程理論與實踐;1999年07期

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本文編號：1463643