Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Input pattern according to standard deviation of backpropagation neural network: Influence on accuracy of soil moisture retrieval

    Access Status
    Fulltext not available
    Authors
    Chai, S.
    Veenendaal, Bert
    West, Geoff
    Walker, J.
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Chai, S. and Veenendaal, B. and West, G. and Walker, J. 2008. Input pattern according to standard deviation of backpropagation neural network: Influence on accuracy of soil moisture retrieval, pp. II691-II694.
    Source Title
    International Geoscience and Remote Sensing Symposium (IGARSS)
    DOI
    10.1109/IGARSS.2008.4779087
    ISBN
    9781424428083
    School
    Department of Spatial Sciences
    URI
    http://hdl.handle.net/20.500.11937/41405
    Collection
    • Curtin Research Publications
    Abstract

    The accuracy of an Artificial Neural Network (ANN) depends on the representativeness of the data used to train it. Although it is known that an ANN will function well as long as the pattern of the input data is similar to the testing data, there has been no research on the effect of data "similarity" on the accuracy of the network outputs. In this paper, an ANN model is used to retrieve soil moisture from the H- and V-polarized brightness temperature obtained. The research discussed in this paper is focused on the standard deviation of the data used for training and testing of the ANN. It is shown that similarity in standard deviation is a good indicator to choose representative training and testing data set. By doing this, the accuracy of retrieval increases from around 22% volume/volume (v/v) of Root Mean Square Error (RMSE) to around 2%(v/v). ©2008 IEEE.

    Related items

    Showing items related by title, author, creator and subject.

    • Colorado geoid computation experiment: overview and summary
      Wang, Y.M.; Sánchez, L.; Ågren, J.; Huang, J.; Forsberg, R.; Abd-Elmotaal, H.A.; Ahlgren, K.; Barzaghi, R.; Bašić, T.; Carrion, D.; Claessens, Sten ; Erol, B.; Erol, S.; Filmer, Mick ; Grigoriadis, V.N.; Isik, M.S.; Jiang, T.; Koç, Ö.; Krcmaric, J.; Li, X.; Liu, Q.; Matsuo, K.; Natsiopoulos, D.A.; Novák, P.; Pail, R.; Pitoňák, M.; Schmidt, M.; Varga, M.; Vergos, G.S.; Véronneau, M.; Willberg, M.; Zingerle, P. (2021)
      The primary objective of the 1-cm geoid experiment in Colorado (USA) is to compare the numerous geoid computation methods used by different groups around the world. This is intended to lay the foundations for tuning ...
    • Fractals and fuzzy sets for modelling the heterogenity and spatial complexity of urban landscapes using multiscale remote sensing data
      Islam, Zahurul (2004)
      This research presents models for the analysis of textural and contextual information content of multiscale remote sensing to select an appropriate scale for the correct interpretation and mapping of heterogeneous urban ...
    • Reducing the dimensionality of hyperspectral remotely sensed data with applications for maximum likelihood image classification
      Santich, Norman Ty (2007)
      As well as the many benefits associated with the evolution of multispectral sensors into hyperspectral sensors there is also a considerable increase in storage space and the computational load to process the data. ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.