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A neural network shortest path algorithm

机译:神经网络最短路径算法

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摘要

This paper develops a neural network implementation of a shortest path algorithm using a Hopfield network architecture. The main advantage of this neural network is that the number of neurons in the network grows linearly with the number of links in the graph instead of growing with the square of the number of nodes in the graph, as is the case with existing algorithms. The properties of this neural network are then investigated and its performance is evaluated through an extensive simulation study.
机译:本文使用Hopfield网络架构开发了最短路径算法的神经网络实现。这种神经网络的主要优势在于,网络中神经元的数量与图中链接的数量成线性增长,而不是像现有算法那样与图中节点数的平方成正比增长。然后研究该神经网络的属性,并通过广泛的仿真研究评估其性能。

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