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    Wyświetlanie 1-2 z 2
    Tytuł:
    Research on general theory and methodology in geodesy in Poland in 2019–2022
    Autorzy:
    Klos, Anna
    Ligas, Marcin
    Trojanowicz, Marek
    Powiązania:
    https://bibliotekanauki.pl/articles/43852778.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    estymacja odporna
    geodezyjne szeregi czasowe
    układ odniesienia
    robust estimation
    relativistic effects
    prediction problems
    datum transformation
    geodetic time series
    Opis:
    We present a summary of research carried out in 2019–2022 in Poland in the area of general theory and methodology in geodesy. The study contains a description of original contributions by authors affiliated with Polish scientific institutions. It forms part of the national report presented at the 28th General Assembly of the International Union of Geodesy and Geophysics (IUGG) taking place on 11-20 July 2023 in Berlin, Germany. The Polish authors developed their research in the following thematic areas: robust estimation and its applications, prediction problems, cartographic projections, datum transformation problems and geometric geodesy algorithms, optimization and design of geodetic networks, geodetic time series analysis, relativistic effects in GNSS (Global Navigation Satellite System) and precise orbit determination of GNSS satellites. Much has been done on the subject of estimating the reliability of existing algorithms, but also improving them or studying relativistic effects. These studies are a continuation of work carried out over the years, but also they point to new developments in both surveying and geodesy.We hope that the general theory and methodology will continue to be so enthusiastically developed by Polish authors because although it is not an official pillar of geodesy, it is widely applicable to all three pillars of geodesy.
    Źródło:
    Advances in Geodesy and Geoinformation; 2023, 72, 1; art. no. e40, 2023
    2720-7242
    Pojawia się w:
    Advances in Geodesy and Geoinformation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    2D Cadastral Coordinate Transformation using extreme learning machine technique
    Autorzy:
    Ziggah, Y. Y.
    Issaka, Y.
    Laari, P. B.
    Hui, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/145372.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    transformacja współrzędnych
    sieci neuronowe
    dane geodezyjne
    sieć radialna
    coordinate transformation
    extreme learning machine
    backpropagation neural network
    radial basis function neural network
    geodetic datum
    Opis:
    Land surveyors, photogrammetrists, remote sensing engineers and professionals in the Earth sciences are often faced with the task of transferring coordinates from one geodetic datum into another to serve their desired purpose. The essence is to create compatibility between data related to different geodetic reference frames for geospatial applications. Strictly speaking, conventional techniques of conformal, affine and projective transformation models are mostly used to accomplish such task. With developing countries like Ghana where there is no immediate plans to establish geocentric datum and still rely on the astro-geodetic datums as it national mapping reference surface, there is the urgent need to explore the suitability of other transformation methods. In this study, an effort has been made to explore the proficiency of the Extreme Learning Machine (ELM) as a novel alternative coordinate transformation method. The proposed ELM approach was applied to data found in the Ghana geodetic reference network. The ELM transformation result has been analysed and compared with benchmark methods of backpropagation neural network (BPNN), radial basis function neural network (RBFNN), two-dimensional (2D) affine and 2D conformal. The overall study results indicate that the ELM can produce comparable transformation results to the widely used BPNN and RBFNN, but better than the 2D affine and 2D conformal. The results produced by ELM has demonstrated it as a promising tool for coordinate transformation in Ghana.
    Źródło:
    Geodesy and Cartography; 2018, 67, 2; 321-343
    2080-6736
    2300-2581
    Pojawia się w:
    Geodesy and Cartography
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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