보로노이 다이어그램

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This type of the Voronoi diagram is defined, and its basic properties are investigated.^[1]
To mathematicians, they are known as Voronoi diagrams.^[2]
Voronoi diagrams are rather natural constructions, and it seems that they, or something like them, have been in use for a long time.^[2]
The beach line is well suited for constructing the Voronoi diagram.^[2]
This means that the breakpoints will sweep out the edges of the Voronoi diagram as the sweep line moves down the plane.^[2]
’s algorithm for computing the Voronoi diagram or Delaunay triangulation of a set of two-dimensional points.^[3]
Given a set of distinct points in , Voronoi diagram is the partition of into polyhedral regions ( ).^[4]
In order to compute the Voronoi diagram, the following construction is very important.^[4]
These problems can both be solved quickly given the Voronoi diagram.^[5]
We present an asymptotically optimal algorithm for computing Voronoi diagrams based on convex distance functions.^[5]
The collection of all Voronoi polygons for every point in the set is called a Voronoi diagram.^[6]
Our goal here is to use a Voronoi diagram to locate the closest bike rack to points of interest in Oxford, OH.^[7]
Laguerre Voronoi Diagram as a Model for Generating the Tessellation Patterns on the Sphere.^[8]
A boundary-partition-based Voronoi diagram of d-dimensional balls: definition, properties, and applications.^[8]
Revisiting Hyperbolic Voronoi Diagrams in Two and Higher Dimensions from Theoretical, Applied and Generalized Viewpoints.^[8]
Voronoi diagram based on a non-convex pattern : an application to extract patterns from a cloud of points.^[8]
Voronoi diagrams, because they are based on how other polygons will be tessellated, can take a long time to computer.^[9]
For typical use, voronoi diagrams can be created by many GIS packages today.^[9]
A raster-based method for computing Voronoi diagrams of spatial objects using dynamic distance transformation.^[9]
A parallel algorithm for constructing Voronoi diagrams based on point-set adaptive grouping: Parallel algorithm for voronoi diagrams.^[9]
Voronoi diagrams are mainly applied to site selection and the determination of the scope of influence of different objects.^[10]
Furtherly, we introduce the Voronoi diagram and the weighted Voronoi diagram to simulate and analyze the ecosystem service areas.^[10]
Compared to traditional Voronoi diagrams, weighted Voronoi diagrams are more suitable for studying ecosystem service coverage.^[10]
ST_VoronoiPolygons computes a two-dimensional Voronoi diagram from the vertices of the supplied geometry.^[11]
-1 indicates vertex outside the Voronoi diagram.^[12]
the number of the Voronoi edges (half-edges) in the Voronoi diagram.^[13]
Voronoi Cell A Voronoi cell represents a region of the Voronoi diagram bounded by the Voronoi edges.^[13]
Second, I compute the Voronoi diagram for this collection of approximating points.^[14]
The remaining Voronoi edges form a good approximation of the generalized Voronoi diagram for the original obstacles in the map.^[14]
In red is the campus map, and in green is the generalized Voronoi diagram computed for this map (which the applet precomputed).^[14]
Click the mouse in the drawing region to add new sites to the Voronoi Diagram or Delaunay Triangulation.^[15]
Voronoi diagrams, or Thiessen polygons, are used to understand patterns over an area of interest.^[16]
Voronoi diagrams are used in a variety of fields for various purposes.^[16]
The space requirement of a graph Voronoi diagram is modest, since it needs no more space than does the graph itself.^[17]
A Voronoi diagram divides a metric space according to the distances between discrete sets of specified objects.^[18]
To solve this, we chose a method to define the cells as the region nearest to each station using a Voronoi diagram.^[19]
The Voronoi diagram is constructed by connecting the center circumcircles of the Delaunay triangles.^[19]
Figure 1 compares conservative remapping using Voronoi diagrams with bilinear interpolation.^[19]
We first constructed the Voronoi diagram from the site locations’ information, using the Python scipy.spatial.^[19]
VDRC is dedicated to study the Voronoi diagram of various kinds for both practical and theoretical view points.^[20]
We are also working on discovering applications of Voronoi diagrams in engineering and science.^[20]
We are particularly interested in solving the structural molecular biology problems using the Voronoi diagram of three-dimensional spheres.^[20]
Figure 1 shows an example of a Voronoi Diagram where each object (denoted by a dot) is placed in a separate polygon.^[21]
In mathematics, a Voronoi diagram is a partition of a plane into regions close to each of a given set of objects.^[22]
Sometimes the induced combinatorial structure is referred to as the Voronoi diagram.^[22]
Informal use of Voronoi diagrams can be traced back to Descartes in 1644.^[22]
In medical diagnosis, models of muscle tissue, based on Voronoi diagrams, can be used to detect neuromuscular diseases.^[22]
Such a map is called a Voronoi diagram, named after Georgy Voronoi, a mathematician born in Ukraine in 1868.^[23]
A Voronoi diagram can be used to find the largest empty circle amid a collection of points, giving the ideal location for the new school.^[23]
He plotted his data on a chart, effectively constructing a Voronoi diagram.^[23]
A Voronoi diagram is sometimes also known as a Dirichlet tessellation.^[24]

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Spacy 패턴 목록

[{'LOWER': 'voronoi'}, {'LEMMA': 'diagram'}]
[{'LOWER': 'voronoi'}, {'LEMMA': 'diagram'}]
[{'LOWER': 'voronoi'}, {'LEMMA': 'polygon'}]
[{'LOWER': 'thiessen'}, {'LOWER': 'polygon'}, {'LEMMA': 'method'}]
[{'LOWER': 'thiessen'}, {'LEMMA': 'polygon'}]

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