首页> 外文会议>2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)论文集 >Research on Particle Swarm Optimization Strategy for Forest Fire Detection System Based on Wireless Sensor Networks
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Research on Particle Swarm Optimization Strategy for Forest Fire Detection System Based on Wireless Sensor Networks

机译:基于无线传感器网络的森林火灾探测系统粒子群优化策略研究

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In order to improve the network performance, to increase network coverage rate, to achieve the maximization of network coverage and extend the network of life in the forest fire detection system, the present research has proposed a Wireless Sensor Networks (WSNs) coverage Particle Swarm Optimization (PSO) strategy on the basis of probability measuring model.Through the PSO, the strategy achieves coverage control for the optimization objectives of network coverage rate and analyzes the effect of coverage performance about sensing radius. The coverage rate has increased and convergence rate has speeded up with perceived radius increased gradually. The simulation shows that effective coverage has reached 85.63 percent. Compared with the Conventional Genetic Algorithms (CGA) about the optimization effectiveness, the coverage rate has increased by 0.64 percent and the convergence rate has increased 13.7 percent.Therefore, the PSO strategy has a better coverage optimization results than CGA.
机译:为了提高森林火灾探测系统的网络性能,提高网络覆盖率,实现网络覆盖率的最大化和延长网络寿命,本研究提出了一种无线传感器网络(WSNs)覆盖率的粒子群算法。 (PSO)策略基于概率测量模型。通过PSO,该策略实现了针对网络覆盖率优化目标的覆盖控制,并分析了覆盖性能对感知半径的影响。随着感知半径的逐渐增加,覆盖率增加并且收敛速度加快。仿真表明,有效覆盖率达到了85.63%。与传统遗传算法(CGA)相比,其覆盖效率提高了0.64%,收敛速度提高了13.7%,因此PSO策略具有比CGA更好的覆盖效果。

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