Artificial neural networks for four-coloring map problems and K-colorability problems
Artificial neural networks for four-coloring map problems and K-colorability problems
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用于四色图问题和 K-可色性问题的人工神经网络
DOI：
10.1109/31.101328
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发表时间：
1991
期刊：
影响因子：
--
通讯作者：
K. C. Lee
中科院分区：
文献类型：
--
作者：
Yoshiyasu Takefuji;K. C. Lee
确定了求解四色映射问题所需的计算能量。提出了一种基于McCulloch-Pits二元神经元模型和Hopfield神经网络的并行算法。结果表明，计算能量总是保证单调递减的牛顿方程。一个4*n的神经元阵列被用来为n个区域的地图着色，其中每个神经元是一个处理元件，根据所提出的牛顿方程执行。该系统的能力，证明了大量的模拟运行。将并行算法推广到求解K-可染性问题。>
The computational energy required for solving a four-coloring map problem is determined. A parallel algorithm for solving the problem based on the McCulloch-Pits binary neuron model and the Hopfield neural network, is presented. It is shown that the computational energy is always guaranteed to monotonically decrease with the Newton equation. A 4*n neural array is used to color a map of n regions, where each neuron is a processing element that performs according to the proposed Newton equation. The capability of this system is demonstrated for a large number of simulation runs. The parallel algorithm is extended for solving the K-colorability problem. >