• DocumentCode
    3020850
  • Title

    Research on multi-sensor data fusion algorithm of soil carbon sink factors based on neural network

  • Author

    Wu Qiulan ; Liang Yong ; Geng Xia ; Xu Hongli

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Agric. Univ., Tai´an, China
  • fYear
    2013
  • fDate
    20-22 Dec. 2013
  • Firstpage
    637
  • Lastpage
    641
  • Abstract
    Accurate acquisition of farmland soil carbon sink factors is the key to realize estimation of soil carbon sink, and development of wireless sensor technology provides an important mean to promotion of measurement accuracy of carbon sink factors. Based on wireless communication protocol, this paper combines cluster-based hierarchical structure with the hierarchical structure of neural network, designs a neural network data fusion algorithm based on cluster-based routing protocol, and uses it in acquisition system of farmland soil carbon sink factors. It is indicated by the results that this algorithm can enhance measurement accuracy of carbon sink factors, reduce data transmission quantity effectively, and decrease energy consumption of the network, thus extend the service life of the network.
  • Keywords
    environmental science computing; farming; neural nets; routing protocols; sensor fusion; soil; wireless sensor networks; cluster-based hierarchical structure; cluster-based routing protocol; data transmission; farmland soil carbon sink factor acquisition; multisensor data fusion algorithm; neural network data fusion algorithm; wireless communication protocol; Carbon; Clustering algorithms; Data integration; Neural networks; Neurons; Soil; Wireless sensor networks; data fusion; multi-sensor; neural network; soil carbon sink;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
  • Conference_Location
    Shengyang
  • Print_ISBN
    978-1-4799-2564-3
  • Type

    conf

  • DOI
    10.1109/MEC.2013.6885142
  • Filename
    6885142