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Elastic neural network method for multi-target tracking task allocation in wireless sensor network

机译:无线传感器网络中多目标跟踪任务分配的弹性神经网络方法

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摘要

Aiming at the task allocation of collaborative technique in wireless sensor network, a method for optimized task allocation based on elastic neural network is proposed under the background of multi-sensor tracking. First a model of multi-coalition tracking multi-target is designed. Then disjoint fully connected subgraphs of neurons are constructed to solve the problem of optimized task allocation in tracking multi-target and the increment of system energy consumption when dynamic coalitions compete and conflict for the resource of sensor nodes. Compared with the conventional method, simulation results show that the energy consumption of the tracking system is reduced significantly and the tracking accuracy is improved greatly, demonstrating the effectiveness of elastic neural network in handling the optimized task allocation problem of multi-sensor tracking multi-target.
机译:针对无线传感器网络中协同技术的任务分配问题,在多传感器跟踪的背景下,提出了一种基于弹性神经网络的任务优化分配方法。首先,设计了一种多联盟跟踪多目标模型。然后构造不相交的全连接神经元子图,以解决动态联盟竞争和冲突的传感器节点资源时,跟踪多目标时优化任务分配以及系统能耗增加的问题。与常规方法相比,仿真结果表明,跟踪系统的能耗大大降低,跟踪精度大大提高,证明了弹性神经网络在处理多传感器跟踪多目标优化任务分配问题上的有效性。 。

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