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A consensus-function artificial neural network for map-coloring

机译:一种用于地图着色的共识函数人工神经网络

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A harmony theory artificial neural network solution to the map coloring problem is presented. Map coloring aims at assigning a unique color to each area of a given map so that no two adjacent areas receive identical colors. The harmony theory implementation is able to determine whether the map coloring problem can be solved with a predefined number of colors as well as which is the smallest number of colors that can solve the map coloring problem. The present implementation directly encodes the given problem into the artificial neural network so that a solution is represented simply by node activation. Additionally, the consensus function of harmony theory produces a quick and definite solution to the colorability problem, obviating the need for manual validation of the result.
机译:提出了一种和谐理论的人工神经网络解决地图着色问题。地图着色的目的是为给定地图的每个区域分配唯一的颜色,以便没有两个相邻的区域接收相同的颜色。和声理论的实现能够确定是否可以使用预定义数量的颜色来解决地图着色问题,以及可以解决地图着色问题的最小数量的颜色。本实施方式将给定问题直接编码到人工神经网络中,从而简单地通过节点激活来表示解决方案。此外,和声理论的共识函数为着色性问题提供了一种快速而确定的解决方案,从而无需人工验证结果。

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