The Use of a Hopfield Neural Network in Solving the Mobility Management Problem

J. Taheri, A. Zomaya
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引用次数: 1

Abstract

This work presents a new approach to solve the location management problem by using the location areas approach. Hopfield Neural Network is used in this work to find the optimal configuration of location areas in a mobile network. Toward this end, the location areas configuration of the network is modeled so that the mobility management cost of the system is related to the energy value of this artificial neural network. Since a pure Hopfield Neural Network was not efficient enough to be used in solving this problem, some modifications applied to it to make it a reasonable approach. Basically, these modifications deal with randomness of selection in manipulating the cells during the solving process. Simulation results are very promising and they lead to network configurations that are unexpected.
Hopfield神经网络在交通管理中的应用
本文提出了一种利用位置区域方法来解决位置管理问题的新方法。本文采用Hopfield神经网络求解移动网络中位置区域的最优配置。为此,对网络的位置区域配置进行建模,使系统的移动性管理成本与该人工神经网络的能量值相关联。由于纯粹的Hopfield神经网络在解决这个问题时效率不够高,因此对其进行了一些修改,使其成为一种合理的方法。基本上,这些修改处理了在求解过程中操纵细胞时选择的随机性。仿真结果非常有希望,它们会导致意想不到的网络配置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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