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A Novel Cuckoo Search Structure Optimized Neural Network for Efficient Data Aggregation in Wireless Sensor Network

机译:无线传感器网络中有效数据聚合的新型布谷鸟搜索结构优化神经网络

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Mobile Wireless Sensor Network (WSN) can be used to solve various issues confronted by static WSN. A mobile sink adheres to diverse mobility patterns in the region of sensors such as controlled mobility, fixed/predictable mobility, and random mobility. Backbone construction can help decrease energy usage. The functioning of sensor nodes needs high levels of energy which are later optimized for the WSN’s effective performance. Optimizers are algorithms utilized to modify the attributes of the neural network, such as weights and learning rates, to decrease the losses. Cuckoo Search (CS), a fairly new metaheuristic, is presently used extensively to resolve various kinds of issues related to optimization. The work examines the new cuckoo search structure optimized neural network Energy-Aware Secure Tree-based Virtual Backbone Network (EAST_VBN) and its ability to minimize the adjustment of energy usage in nodes to improve the WSN’s network lifetime.
机译:移动无线传感器网络(WSN)可用于解决静态WSN面临的各种问题。移动接收器在传感器区域遵循各种移动性模式,例如受控移动性,固定/可预测移动性和随机移动性。骨干结构可以帮助减少能源消耗。传感器节点的功能需要高水平的能量,后来又针对WSN的有效性能进行了优化。优化器是用于修改神经网络属性(例如权重和学习率)以减少损失的算法。布谷鸟搜索(Cuckoo Search,CS)是一种相当新的元启发式方法,目前被广泛用于解决与优化有关的各种问题。这项工作研究了新的布谷鸟搜索结构,优化了神经网络,基于神经网络的基于能量感知的基于安全树的虚拟骨干网络(EAST_VBN)及其最小化节点能耗调整以提高WSN网络寿命的能力。

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