CAJ | 학술논문

针对基于标准粒子群算法的网络覆盖存在收敛速度慢、易早熟等问题,提出一种基于遗传 PSO 的无线传感网络覆盖优化算法.以无线传感器最大覆盖率为目标函数,通过运用加入自适应交叉变异因子的遗传算法搜索解空间,利用 PSO 粒子群强大的全局搜索能力加大搜索范围,使粒子覆盖更有效率,加强算法的寻优能力,提高节点的覆盖率,解决早熟问题.仿真实验表明,与传统遗传算法、新量子遗传算法相比,其覆盖率分别提高了2.28%和0.65%,收敛速度也有所提高,因此该方法能有效地实现无线传感网络覆盖优化.
침대기우표준입자군산법적망락복개존재수렴속도만、역조숙등문제,제출일충기우유전 PSO 적무선전감망락복개우화산법.이무선전감기최대복개솔위목표함수,통과운용가입자괄응교차변이인자적유전산법수색해공간,이용 PSO 입자군강대적전국수색능력가대수색범위,사입자복개경유효솔,가강산법적심우능력,제고절점적복개솔,해결조숙문제.방진실험표명,여전통유전산법、신양자유전산법상비,기복개솔분별제고료2.28%화0.65%,수렴속도야유소제고,인차해방법능유효지실현무선전감망락복개우화.
@@@@According to the standard particle swarm algorithm based on the existing network cover slow convergence speed ,easy early ,is proposed based on the genetic PSO of wireless sensor network coverage optimization algorithm . In wireless sensor maximum coverage as the objective function ,through the application of join adaptive crossover and mutation factor genetic algorithm to search the solution space ,using the PSO (particle swarm optimization ) powerful global search ability increase search scope , make particle cover more efficient , strengthen algorithm optimization ability ,improve the node coverage ,solve premature problem .Simulation results show that ,with the standard traditional genetic algorithm ,the PSO algorithm optimization results were compared ,and the coverage increased by 2 .28% and 0 .65% respectively ;and convergence speed increased ,so this method can effectively realize the wireless sensor network coverage optimization .