[1]王金鑫,秦子龙,曹泽宁,等.基于八叉树的修正克里金空间插值算法[J].郑州大学学报(工学版),2021,42(06):22-28.
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基于八叉树的修正克里金空间插值算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
42
期数:
2021年06期
页码:
22-28
栏目:
出版日期:
2021-11-10

文章信息/Info

Title:
Adaptive modified Kriging spatial interpolation algorithm considering distribution equilibrium
作者:
王金鑫秦子龙曹泽宁陈艺航石焱
文献标志码:
A
摘要:
针对空间插值算法中需合理设置待插值点的邻域搜索,并考虑空间分布问题,本文提出了一种基于八叉树的空间插值邻域搜索策略。首先,构建采样点的最小外包围盒并对其进行八叉树剖分,将采样点各自归于剖分后的包围盒中;然后,对待插值点进行邻域点搜索,并通过定义点密度来约束待插值点的空间分布;最后,对于空间内任意待插点,将上述的邻域搜索策略应用到普通克里金插值模型中进行空间插值,并将本文方法与传统的空间插值方法进行对比实验。结果表明:本文方法在插值精度与效率上均优于传统方法,且能保证插值点在空间分布的均匀性,数据冗余较少,可应用于各类基于离散点的空间插值场景与插值算法中,是一种可靠的空间插值算法。
Abstract:
In this paper, an octree ba<x>sed spatial interpolation strategy is proposed to solve the problem of neighborhood search and spatial distribution of points. First, the minimal enclosing box of the sampling points is constructed and divided with octree, and the sampling points are grouped into each enclosing box. Then, the spatial distribution of the interpolating points is constrained by defining the point density. Finally, for at any point in the space, the above neighborhood search strategy is applied to the ordinary Kriging interpolation model for spatial interpolation , and a comparative experiment between the method in this paper and the traditional spatial interpolation method s is carried out. The results show that the method in this paper is superior to traditional methods in terms of interpolation accuracy and efficiency with less data redundancy. It can guarantee the uniformity of interpolation points in spatial distribution. Therefore, it is a reliable spatial interpolation algorithm, and can be applied to various spatial interpolation scenes and algorithms ba<x>sed on discrete points
更新日期/Last Update: 2021-12-17