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首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks
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An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks

机译:基于内分泌的智能分布式协作算法在无线传感器网络中的目标跟踪

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摘要

In this paper, a novel endocrine-based intelligent distributed cooperative algorithm (EIDCA) for target tracking is proposed inspired by the regulating mechanisms of the human hormone systems. The EIDCA enables the nodes in the wireless sensor networks to self-organize themselves autonomously without a centralized control for target detection. A probability-based scheme for hormone transmission is also introduced to alleviate fluctuations of the network caused by frequent switches of the nodes. Meanwhile, a numerical evaluation method is designed to provide a quantitative metric for comparing the tracking performance of different algorithms. Simulation results show that the decentralized network controlled by the EIDCA can work efficiently and reliably without central control. It is also shown that the proposed EIDCA outperforms the compared algorithms in tracking targets.
机译:在本文中,受人荷尔蒙系统的调节机制的启发,提出了一种新颖的基于内分泌的智能分布式合作算法(EIDCA)进行目标跟踪。 EIDCA使无线传感器网络中的节点能够自动进行自我组织,而无需集中控制目标检测。还引入了一种基于概率的激素传输方案,以缓解由于节点频繁切换而引起的网络波动。同时,设计了一种数值评估方法,以提供一种量化指标,用于比较不同算法的跟踪性能。仿真结果表明,由EIDCA控制的分散网络无需中央控制就能高效,可靠地工作。还表明,提出的EIDCA在跟踪目标方面优于已比较的算法。

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