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Application of different radial basis function networks in the illegal waste dump-surface modelling

Author

Listed:
  • Polona Pavlovčič-Prešeren

    (University of Ljubljana)

  • Bojan Stopar

    (University of Ljubljana)

  • Oskar Sterle

    (University of Ljubljana)

Abstract

In quality assessment of digital elevation models (DEMs), geodetic field measurements have an important, but also a limited, role. They can achieve high accuracy, but the acquisition of data is time consuming, expensive and, in areas with a high-resolution DEM accessibility, non-effective. Therefore, field measurements are only performed at discrete selected points to evaluate the quality of the DEM used for further studies. The aim of this article is to show that differences in heights from field measurements and from a DEM can be used for height-deviation-surface modelling and for possible improvements in the available DEM. The procedure is related to situations where significant changes in the landscape occur. For surface modelling, this research included several radial basis function networks (RBFNs). From simulations, knowledge was acquired of appropriate results based on varying amounts of input data as well as on different neural network activation functions. This study indicates the potential use of geodetic field measurements in the improvement of a local DEM by RBFNs.

Suggested Citation

  • Polona Pavlovčič-Prešeren & Bojan Stopar & Oskar Sterle, 2019. "Application of different radial basis function networks in the illegal waste dump-surface modelling," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 783-795, September.
    • Handle: RePEc:spr:cejnor:v:27:y:2019:i:3:d:10.1007_s10100-018-0586-z
    DOI: 10.1007/s10100-018-0586-z
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    References listed on IDEAS

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    1. Stefan Giebel & Martin Rainer, 2013. "Neural network calibrated stochastic processes: forecasting financial assets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(2), pages 277-293, March.
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    Cited by:

    1. Andrea Furková, 2022. "Implementation of MGWR-SAR models for investigating a local particularity of European regional innovation processes," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 733-755, June.
    2. Andrej Kastrin & Janez Povh & Lidija Zadnik Stirn & Janez Žerovnik, 2021. "Methodologies and applications for resilient global development from the aspect of SDI-SOR special issues of CJOR," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 773-790, September.

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