基于双层递归神经网络的路由优化算法
Routing Algorithm Based on Two-layer Recurrent Neural Network
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摘要: 研究分组交换网的路由选择及流量分配问题，以网络的平均时延为优化目标函数。为使问题的解能实时、可靠地完成，将一种用于最短路径计算的双层递归神经网络应用于路由选择的流量导数法中。仿真结果表明，该算法在收敛的可靠性和计算的实时性方面有所提高。Abstract: This paper is concerned with the optimum routing and flow assignment problem in packet-switch networks. The optimum objective function is the network-wide average time delay. To make the solution be implemented reliably in real time, a neural network for shortest path computation that is a two-layer recurrent structure is applied to flow deviation method. Simulation results show that improvements can be achieved in the reliability of successful convergence and in the decrease of computation time.
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