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A Study on Water Pollution Source Localization in Sensor Networks

机译:传感器网络水污染源定位研究

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摘要

The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.
机译:水污染源定位对水环境保护具有重要意义。本文介绍了水污染源定位的研究。首先,讨论源检测。然后,分别介绍和分析基于扩散模型的粗糙定位方法和定位方法。另外,提出了基于轮廓的定位方法。最终将检测和定位方法与实验进行比较。结果表明,使用假设测试的检测方法更稳定。粗糙定位算法的性能取决于节点密度。基于扩散模型的定位可以产生精确的定位结果;但是,结果不稳定。基于轮廓的定位方法优于浓度轮廓是轴对称时的其他两个定位方法。因此,在水污染源定位中,在源检测步骤中更优选使用假设测试的检测。如果浓度轮廓是轴对称的,则基于轮廓的定位方法是第一个选项。并且,如果节点密集并且没有明确的扩散模型,则可以使用粗略定位算法,或者基于扩散模型的定位是一个不错的选择。

著录项

  • 作者

    Jun Yang; Xu Luo;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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