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Localization algorithms in wireless sensor networks using nonmetric multidimensional scaling with RSSI for precision agriculture

机译:无线传感器网络中的本地化算法使用RSSI进行无需多维多维缩放进行精密农业

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The positions of the sensor nodes in wireless sensor networks for precision agriculture must be required first. Position estimation generally includes errors due to the measurements of distance. Erroneous positions are propagated from a node to other nodes exacerbating the degree of errors in the estimation of the positions of these nodes. In this study, we evaluated the performance of NMDS-RSSI localization algorithms, using data from scenarios in farm. We concluded that the average value of the localization error deceased with signal propagation coefficient-???????? increasing. And we proved the robust of NMDS algorithm for bad environment. Moreover, we obtained the relationship between the localization error and connectivity. The simulations show that the NMDS-RSSI localization algorithms yields better performance than the MDS-MAP in the same simulation conditions.
机译:首先必须要求传感器节点在无线传感器网络中进行精密农业的位置。 位置估计通常包括由于距离的测量而导致的误差。 错误的位置从节点传播到更快地加剧这些节点的位置中的错误程度的其他节点。 在这项研究中,我们评估了NMDS-RSSI本地化算法的性能,使用来自场场景的数据。 我们得出结论,定位错误的平均值与信号传播系数死了 - ???????? 增加。 并且我们证明了对不良环境的NMDS算法的强大。 此外,我们获得了本地化误差和连接之间的关系。 仿真表明,NMDS-RSSI定位算法比在相同的模拟条件下的MDS-MAP产生更好的性能。

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