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Implementation of a Web interface for hybrid intelligent systems A comparison study of two hybrid intelligent systems

机译:混合智能系统Web接口的实现两种混合智能系统的比较研究

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Purpose - The purpose of this paper is to implement a Web interface for hybrid intelligent systems. Using the implemented Web interface, this paper evaluates two hybrid intelligent systems based on particle swarm optimization, hill climbing and distributed genetic algorithm to solve the node placement problem in wireless mesh networks (WMNs). Design/methodology/approach - The node placement problem in WMNs is well-known to be a computationally hard problem. Therefore, the authors use intelligent algorithms to solve this problem. The implemented systems are intelligent systems based on meta-heuristics algorithms: Particle Swarm Optimization (PSO), Hill Climbing (HQ and Distributed Genetic Algorithm (DGA). The authors implement two hybrid intelligent systems: WMN-PSODGA and WMN-PSOHC-DGA. Findings - The authors carried out simulations using the implemented Web interface. From the simulations results, it was found that the WMN-PSOHC-DGA system has a better performance compared with the WMN-PSODGA system. Research limitations/implications - For simulations, the authors considered Normal distribution of mesh clients. In the future, the authors need to consider different client distributions, patterns, number of mesh nodes and communication distance. Originality/value - In this research work, the authors implemented a Web interface for hybrid intelligent systems. The implemented interface can be extended for other metaheuristic algorithms.
机译:目的-本文的目的是为混合智能系统实现Web界面。本文使用已实现的Web界面,评估了两个基于粒子群优化,爬山和分布式遗传算法的混合智能系统,以解决无线网状网络(WMN)中的节点放置问题。设计/方法/方法-WMN中的节点放置问题是众所周知的计算难题。因此,作者使用智能算法来解决此问题。实现的系统是基于元启发式算法的智能系统:粒子群优化(PSO),爬山(HQ)和分布式遗传算法(DGA),作者实现了两个混合智能系统:WMN-PSODGA和WMN-PSOHC-DGA。发现-作者使用已实现的Web界面进行了仿真,从仿真结果中发现,与WMN-PSODGA系统相比,WMN-PSOHC-DGA系统具有更好的性能。作者考虑了网格客户端的正态分布,将来,作者需要考虑不同的客户端分布,模式,网格节点数和通信距离原创性/价值-在这项研究中,作者实现了混合智能系统的Web界面可以将实现的接口扩展为其他元启发式算法。

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