hopfield神经网络模型及计算机网络中路由最短路径计算的启发式算法的关键分析

Farah Sarwar, A. A. Bhatti
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引用次数: 3

摘要

最短路径路由及其计算是计算机网络中的一个关键问题,对整个网络的性能有着重要的影响。作为一个非常重要的问题,人们提出了许多用于最短路径计算的算法,并且还在研究中进行进一步的改进。Hopfield针对这类优化问题提出了一种基于神经网络的体系结构。Mehmet和Park Keum建议改进该神经网络的能量函数,以便在计算机网络中实现路由。A*搜索算法是一种基于启发式的方法,具有Dijikstra算法的特性,用于相同的目的。比较了两种方法的性能,并对结果进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Critical analysis of hopfield's neural network model and heuristic algorithm for shortest path computation for routing in computer networks
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.
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