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首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods
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Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods

机译:基于粒子群优化和模拟退火的WMN智能混合仿真系统的实现:不同替代方法的性能评估

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摘要

Wireless mesh networks (WMNs) have many advantages such as low-cost and increased high- speed wireless Internet connectivity; therefore, WMNs are becoming an important networking infrastructure. In our previous work, we implemented a particle swarm optimization (PSO)-based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on simulated annealing (SA) called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the performance of WMN-PSOSA by conducting computer simulations considering four different replacement methods. The simulation results show that the rational decrement of Vmax method and linearly decreasing inertia weight method have better performance compared with constriction method and random inertia weight method.
机译:无线网状网络(WMN)具有许多优点,如低成本,高速无线互联网连接增加; 因此,WMN正在成为一个重要的网络基础设施。 在我们以前的工作中,我们实现了用于WMN中的节点放置的粒子群优化(PSO)的仿真系统,称为WMN-PSO。 此外,我们通过称为WMN-SA的模拟退火(SA)实现了一种仿真系统。 在本文中,我们实施了基于PSO和SA的混合仿真系统,称为WMN-PSOSA。 考虑到四种不同的替代方法,我们通过进行计算机模拟来评估WMN-PSOSA的性能。 仿真结果表明,与收缩方法和随机惯性重量法相比,VMAX方法的合理减少和线性降低的惯性重量方法具有更好的性能。

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