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An extension of regression-based automatic calibration method for sensor networks

机译:基于回归的传感器网络自动校准方法的扩展

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This work proposes a new automatic calibration method for the sensor network which measures the distribution of physical fields. In case of these sensor networks, the regular calibration of the sensors is necessary for obtaining reliable information. However, it is not an easy task in the case of a large scale sensor network, because the manual calibration is time consuming and costly. To solve this problem, this present study proposes a new method which is based on the two concepts of regression analysis and cross validation. In this paper, the new method is explained and the efficient extension is also proposed, and the performance of the proposed methods is verified by a simulation.
机译:这项工作提出了一种用于测量物理字段分布的传感器网络的新型自动校准方法。在这些传感器网络的情况下,传感器的常规校准是获得可靠信息所必需的。但是,在大规模传感器网络的情况下,它不是一件容易的任务,因为手动校准是耗时且昂贵的。为了解决这个问题,本研究提出了一种基于回归分析和交叉验证的两种概念的新方法。在本文中,解释了新方法,还提出了有效的扩展,并通过模拟验证了所提出的方法的性能。

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