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Critical analysis of hopfield's neural network model and heuristic algorithm for shortest path computation for routing in computer networks

机译:Hopfield的神经网络模型和启发式算法在计算机网络中路由中最短路径计算的批判性分析

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Shortest path routing and its computation is a crucial point in computer networks, and has significant impact on overall network's performance. Being an issue of salient importance, many algorithms were proposed for shortest path computation and are still under research for more enhancements. Hopfield proposed a neural network based architecture for such optimization problems. Mehmet and Park Keum suggested improved energy functions for this neural network to implement it for routing in computer networks. A* search algorithm is a heuristic based approach, with the properties of Dijikstra algorithm and is used for same purpose. Performances of both approaches are compared and results are analyzed.
机译:最短路径路由及其计算是计算机网络的关键点,对整体网络的性能产生重大影响。 作为突出的重要性,提出了许多算法,以获得最短路径计算,并且仍在研究更多的增强功能。 Hopfield提出了一种基于神经网络的基于神经网络的架构进行这种优化问题。 Mehmet和Park Keum建议改进该神经网络的能量功能,以实现在计算机网络中路由的方式。 a *搜索算法是一种基于启发式的方法,具有Dijikstra算法的属性,用于相同目的。 比较两种方法的性能并分析结果。

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