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Shortest path routing algorithm based on chaotic neural network

机译:基于混沌神经网络的最短路径路由算法

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摘要

A shortest path routing algorithm based on transient chaotic neural network is proposed in this paper. Compared with previous models adopting Hopfield neural network, this algorithm has a higher ability to overcome the local minimum, and achieves a better performance. By introducing a special post-processing technique for the output matrixes, our algorithm can obtain an optimal solution with a high probability even for the paths that need more hops in large-sizenetworks.
机译:提出了一种基于瞬态混沌神经网络的最短路径路由算法。与以前采用Hopfield神经网络的模型相比,该算法具有更高的克服局部极小值的能力,并具有更好的性能。通过为输出矩阵引入特殊的后处理技术,即使对于大型网络中需要更多跃点的路径,我们的算法也可以以高概率获得最优解。

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