The Research On The Query Of Uncertainty Of Three-dimensional Objects

With the continuous development of geographic information systems,the application of spatial information is also extended.It has been widely used in urban planning,transportation hubs,virtual reality and other fields,and its value is becoming more and more important.However,due to the limitation of space processing technology or the insufficiency of spatial data acquisition equipment,unpredictable systematic errors or random errors may occur in every step of acquiring spatial data,which is inevitable.At the same time,due to the influence of the surrounding environment,the uncertainty of data collection will be caused in the data collection stage inevitably.Therefore,spatial data is generally uncertain.Uncertainty is widespread in the process of using spatial data to assist humans in making decisions,such as urban planning or trajectory prediction.Only by understanding these uncertainties brought about by spatial data can man-made risks be minimized.With the research on various types of uncertainty queries in three-dimensional space,there are deficiencies in the research results in dealing with some uncertainty query problems;at the same time,there is a lack of correctness in the relevant content that takes the uncertainty query problem as the research object.The three-dimensional uncertainty query problem is comprehensively and systematically discussed by related researches.In this dissertation,the main research content of the spatial database field is problems that may occur in various steps of the three-dimensional space object,including the query problem of the uncertain shape of the three-dimensional object,the query problem of the uncertain position and the spatial direction relationship,and the uncertain attribute.The main research contents are as follows:Firstly,to solve the problem of representation and indexing of uncertain shape of objects in three-dimensional space effectively,a C-k OBB bounding box structure based on improved OBB bounding box is proposed.The construction process of C-k OBB bounding box is explained in detail,the advantages of the index structure of three-dimensional objects with uncertain morphology are analyzed.On this basis,a hierarchical tree index structure based on the C-k OBB bounding box is proposed,and its advantages in query efficiency compared with the traditional R-tree index structure are analyzed.It is verified that it can perform efficient indexing and query speed for objects with uncertain shapes in three-dimensional space quickly and accurately,and pave the way for the uncertainty-related query problems studied in the following chapters.Secondly,considering the uncertain shape of objects in three-dimensional space,the probabilistic visual k nearest neighbor query algorithm which named 3D-PVk NN and the group reverse k farthest neighbor query algorithm which named V-OGRk FN are proposed.For each query algorithm,a spatial pruning strategy and corresponding algorithm are proposed respectively.By designing effective rules and pruning strategies,some of the objects that cannot become the result are eliminated,avoiding participation in a large number of subsequent calculations.Finally,the implementation and analysis of3D-PVk NN query algorithm and V-OGRk FN query algorithm are given.The two query algorithms take the uncertain shape of three-dimensional objects and the uncertain influence caused by obstacles into account,and meet the query requirements in realistic three-dimensional obstacle scenes.Thirdly,aiming at the uncertainty of position and direction relationship query problem of the three-dimensional object,a 3D-ICSRM model is proposed and constructed.The construction process of the model is explained and introduced in detail,and the advantages of the 3D-ICSRM model are fully analyzed.Then,the inference principle of uncertain position and spatial direction relationship based on 3D-ICSRM model and the query algorithm HPSRA are proposed,which shows the advantages of 3D-ICSRM model in the query of uncertain position and direction relationship of three-dimensional objects.Fourthly,aiming at the problem of uncertain attributes’ s query that three-dimensional objects are susceptible to interference caused by human factors,a skyline query research which based on fuzzy theory is proposed.First at all,a comprehensive evaluation algorithm for uncertain attribute data is proposed.The fuzzy membership degree and comprehensive evaluation result set are used to express the influence of uncertain attributes in the query operation;then,the obstacle distance in the obstacle environment and other factors are considered comprehensively,and the skyline-like query algorithm which named UASQA is proposed.The filtering and pruning processes have been designed to eliminate objects which affect the results,and it improves the query speed efficiency by reducing the size of objects to be calculated.Finally,a three-dimensional object experiment of uncertainty query is designed,including the uncertain shape object query experiment,the uncertain position and spatial direction relationship query experiment,and the uncertain attribute data query experiment,and then proposed the combination query method of multi-factor uncertainty of the three-dimensional object.The advantages of each query algorithm are analyzed,and the correctness of the uncertainty query theory for three-dimensional space objects proposed in this dissertation are verified,which met the query requirements of three-dimensional space scenes for uncertain problems.