TY -的A2 -加索尔,乔凡尼盟,哈比比Payman盟——Hassanifard Goran盟——Ghaderzadeh Abdulbaghi盟——Nosratpour Arez PY - 2023 DA - 2023/05/02 TI -提供需求导向的充电方法使用GBO算法和模糊逻辑WRSN无人机无线电力传输的SP - 6326423六世- 2023 AB -极其大量地理上分散的,能源有限公司传感器节点组成的无线传感器网络。这些网络的关键困难之一是他们的网络的生命周期。无线充电的传感器不断是一个技术来延长网络的寿命。为了弥补传感器节点的能量通过无线介质,手机充电器(MC)是用于无线传感器网络(WRSN)。最好设计一个充电方案,延长网络的生命周期在这种情况下是很困难的。需求导向的充电方法,使用无人机(uav)提供无线充电传感器网络。在这方面,首先,传感器被分组根据其地理位置使用k - means聚类技术。然后,借助一个模糊逻辑系统,这些集群排名的顺序优先级参数的基础上电池寿命的平均比例在传感器节点的电池、传感器的数量和关键传感器必须充电,每个集群中心之间的距离和MC充电站。然后显示无人机的位置选择关键传感器节点使用一个路由算法基于每个集群的最短和最重要的路径。值得注意的是,基于的梯度优化(GBO)算法已经应用于这项工作的星团内路由。 A case study for a wireless rechargeable sensor network has been carried out in MATLAB to assess the performance of the suggested design. The outcomes of the simulation show that the suggested technique was successful in extending the network’s lifetime. Based on the simulation results, compared to the genetic algorithm, the proposed algorithm has been able to reduce total energy consumption, total distance during the tour, and total travel delay by 26%, 17.2%, and 25.4%, respectively. SN - 1687-725X UR - https://doi.org/10.1155/2023/6326423 DO - 10.1155/2023/6326423 JF - Journal of Sensors PB - Hindawi KW - ER -