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An Improved Three-dimensional DV-Hop Localization Algorithm Optimized by Adaptive Cuckoo Search Algorithm

机译:自适应杜鹃搜索算法优化的改进三维DV-Hop定位算法

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Aiming at the low accuracy of DV-Hop localization algorithm in three-dimensional localization of wireless sensor network, a DV-Hop localization algorithm optimized by adaptive cuckoo search algorithm was proposed in this paper. Firstly, an improved DV-Hop algorithm was proposed, which can reduce the localization error of DV-Hop algorithm by controlling the network topology and improving the method for calculating average hop distance. Meanwhile, aiming at the slow convergence in traditional cuckoo search algorithm, the adaptive strategy was improved for the step search strategy and the bird's nest recycling strategy. And the adaptive cuckoo search algorithm was introduced to the process of node localization to optimize the unknown node position estimation. The experiment results show that compared with the improved DV-Hop algorithm and the traditional DV-Hop algorithm, the DV-Hop algorithm optimized by adaptive cuckoo search algorithm improved the localization accuracy and reduced the localization errors.
机译:针对无线传感器网络三维定位中DV-Hop定位算法精度低的问题,提出了一种采用自适应布谷鸟搜索算法优化的DV-Hop定位算法。首先,提出了一种改进的DV-Hop算法,通过控制网络拓扑结构和改进平均跳距的计算方法,可以减少DV-Hop算法的定位误差。同时,针对传统布谷鸟搜索算法的收敛速度较慢的情况,对步搜索策略和燕窝回收策略进行了改进。将自适应布谷鸟搜索算法引入到节点定位过程中,以优化未知节点的位置估计。实验结果表明,与改进的DV-Hop算法和传统的DV-Hop算法相比,自适应布谷鸟搜索算法优化的DV-Hop算法提高了定位精度,减少了定位误差。

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