Research On Skyline Group Query In Three-dimensional Obstacle Space

Skyline query,as a typical multi-objective optimization problem,plays an important role in decision when there are many multi-factor conditions.Since it was proposed,it has attracted extensive attention of researchers,and researches in related directions have also been continuously expanded,such as the single point query of Skyline,spatial Skyline query,k-dominated Skyline query and probability Skyline query.Skyline group query is an important extension of Skyline query in multi-objective optimization.However,there are few related studies on Skyline group,and the previous literature did not classify the target attributes,which will lead to some spatial characteristics being ignored when it comes to spatial attributes.To solve the above problems,a Group Representing Skyline query with partition attributes is proposed.Moreover,different solutions in 2d Euclidean space and 3D obstacle space are given.This paper carries out a detailed study on the Group Representative Skyline query.The main researchs are as follows.First,a Group Representative Skyline query for two-dimensional space is proposed.This paper introduces the research background and significance of this query.In order to solve this kind of query problem,the concept of group representation dominance is put forward,and the attributes of data points are classified.According to the fuzzy comprehensive evaluation theory and the user’s personal preference,the non-spatial attributes of Skyline points in the group will be evaluated.Then,the algorithm for querying the group representative Skyline will be given to return the data set that is not dominated by other groups.Secondly,a Group Represenative Skyline query in 3d obstacle space is proposed.It is mainly committed to solving the group Skyline query problem in 3d obstacle space,and based on the group representative Skyline query in 2d space,it continues its relevant algorithm on non-spatial attributes.In the three-dimensional obstacle space,the influence of obstacles is fully considered when calculating the distance,and the obstacles are pruned in advance to obtain the selection of obstacle phenology,and then the three-dimensional viewable is constructed to solve the obstacle distance.After that,Voronoi diagram in threedimensional space is constructed and relevant calculation is carried out on this basis.In this paper,the algorithm implementation and detailed algorithm analysis of obstacle group representation Skyline query are given.Finally,experiments are carried out on the two groups representing Skyline query algorithms proposed above.Firstly,the traditional Skyline group algorithm PWise is set as the comparison test for the group representing Skyline query in two-dimensional space.Secondly,since none of the previous algorithms involved three-dimensional obstacle space,an internal comparison experiment is conducted on the obstacle group representative Skyline query algorithm,and relevant performance indexes of the algorithm are recorded and analyzed.The experimental results show that the two algorithms presented in this paper have good performance.