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Comparisons of seven neural network models on traffic control problems in multistage interconnection networks

机译:七种神经网络模型在多级互连网络中流量控制问题的比较

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摘要

The performances of seven neural network models for traffic control problems in multistage interconnection networks are compared. The decay term, three neuron models, and two heuristics were evaluated. The goal of the traffic control problems is to find conflict-free switching configurations with the maximum throughput. The simulation results show that the hysteresis McCullock-Pitts neuron model without the decay term and with two heuristics has the best performance.
机译:比较了多级互连网络中用于流量控制问题的七个神经网络模型的性能。衰减项,三个神经元模型和两个启发式进行了评估。流量控制问题的目标是找到具有最大吞吐量的无冲突交换配置。仿真结果表明,没有衰减项并具有两种启发式的磁滞McCullock-Pitts神经元模型具有最佳性能。

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