THE N-DIMENSIONAL MAP MAKER ALGORITHM

J. Rankin
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引用次数: 1

Abstract

The Map Maker algorithm which converts survey data into geometric data with 2-dimensional Cartesian coordinates has been previously published. Analysis of the performance of this algorithm is continuing. The algorithm is suitable for generating 2D maps and it would be helpful to have this algorithm generalized to generate 3D and higher dimensional coordinates. The trigonometric approach of the Map Maker algorithm does not extend well into higher dimensions however this paper reports on an algebraic approach which solves the problem. A similar algorithm called the Coordinatizator algorithm has been published which converts survey data defining a higher dimensional space of measured sites into the lowest dimensionalcoordinatization accurately fitting the data. Therefore the Coordinatizator algorithm is not a projection transformation whereas the n-dimensional Map Maker algorithm is.
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n维地图制作算法
Map Maker算法将测量数据转换为具有二维笛卡尔坐标的几何数据,该算法此前已发表。对该算法性能的分析还在继续。该算法适用于二维地图的生成,将该算法推广到三维及高维坐标的生成将有很大帮助。Map Maker算法的三角方法不能很好地扩展到高维,但本文提出了一种代数方法来解决这一问题。一种类似的算法被称为坐标算法,它将测量数据转换为定义测量站点的高维空间的最低维坐标,以准确地拟合数据。因此,coordinator算法不是投影变换,而n维Map Maker算法是。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
4
审稿时长
>12 weeks
期刊介绍: The International Journal of Computational Geometry & Applications (IJCGA) is a quarterly journal devoted to the field of computational geometry within the framework of design and analysis of algorithms. Emphasis is placed on the computational aspects of geometric problems that arise in various fields of science and engineering including computer-aided geometry design (CAGD), computer graphics, constructive solid geometry (CSG), operations research, pattern recognition, robotics, solid modelling, VLSI routing/layout, and others. Research contributions ranging from theoretical results in algorithm design — sequential or parallel, probabilistic or randomized algorithms — to applications in the above-mentioned areas are welcome. Research findings or experiences in the implementations of geometric algorithms, such as numerical stability, and papers with a geometric flavour related to algorithms or the application areas of computational geometry are also welcome.
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