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The closest pair of points problem or closest pair problem is a problem of computational geometry: given points in metric space, find a pair of points with the smallest distance between them. The closest pair problem for points in the Euclidean plane [ 1 ] was among the first geometric problems that were treated at the origins of the systematic ...
Closest pair of points problem, the algorithmic problem of finding two points that have the minimum distance among a larger set of points; Euclidean distance, the minimum length of any curve between two points in the plane; Shortest path problem, the minimum length of a path between two points in a graph
For a given set of points S = {p 1, p 2, ..., p n}, the farthest-point Voronoi diagram divides the plane into cells in which the same point of P is the farthest point. A point of P has a cell in the farthest-point Voronoi diagram if and only if it is a vertex of the convex hull of P .
In the bichromatic closest pair problem, the input is a set of points, given two different colors (say, red and blue). The output is a pair of a red point and a blue point with the minimum possible distance. This pair always forms one of the edges in the minimum spanning tree.
Proximity problems is a class of problems in computational geometry which involve estimation of distances between geometric objects.. A subset of these problems stated in terms of points only are sometimes referred to as closest point problems, [1] although the term "closest point problem" is also used synonymously to the nearest neighbor search.
A problem in solving partial differential equations using previous methods is that the grid is constructed and the points are distributed in the physical domain before details of the solution is known. So the grid may or may not be the best for the given problem. [8] Adaptive methods are used to improve the accuracy of the solutions. The ...
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For a given set of points in space, a Voronoi diagram is a decomposition of space into cells, one for each given point, so that anywhere in space, the closest given point is inside the cell. This is equivalent to nearest neighbor interpolation, by assigning the function value at the given point to all the points inside the cell. [3]