PERPUSTAKAAN BIG

  • Beranda
  • Informasi
  • Berita
  • Bantuan
  • Area Pustakawan
  • Area Anggota
  • Pilih Bahasa :
    Bahasa Arab Bahasa Bengal Bahasa Brazil Portugis Bahasa Inggris Bahasa Spanyol Bahasa Jerman Bahasa Indonesia Bahasa Jepang Bahasa Melayu Bahasa Persia Bahasa Rusia Bahasa Thailand Bahasa Turki Bahasa Urdu
Image of The 1st International Workshop on the Quality of geodesy observation andmonitoring system (QuGOMS'11) Proceddings of the 2001 IAG International Workshop, Munich, Germany, April 13-15,2011

Text

The 1st International Workshop on the Quality of geodesy observation andmonitoring system (QuGOMS'11) Proceddings of the 2001 IAG International Workshop, Munich, Germany, April 13-15,2011

Lynn E. Johnson - Nama Orang; Hansjorg Kutterer, Florian Seitz - Nama Orang; Hamza Alkhatib - Nama Orang; Michael Schmidt - Nama Orang;

This paper focuseson the modelingof data quality in processes which are in general not knowndetail or which are too complex to describe all influences on data quality. Asemerged during research, artificial neural networks (ANN) are capable formodeling data qualitparameters within processes with respect to their interconnections. Since multi-layer feed forward ANN are required forthis task a large number of examples, depending on the number ofquality parameters to be taken into account, is necessaryfor the suppervised learning of the ANN,respectively determining all parameters defining the net. Therefore the general usability of ANN was firstly evaluated for asimple geodetic application, the polar survey, where an unlimited number of learning examples could be generated easily. Aswill be shown, the quality parameters describing accuracy, availability, completenessor consistency and accuracy was tested as well. Standard deviations of new points can be determined using ANN wit-mm accurcy in all cases. To benchmark the usability of ANN forareal practical the complex process of mobile radio location and determination of driver trajectories on the digital road network based on these data, was used, The quality of calculated trajectories couiently from a number of relevan input parameters such ld be predicted sufficas antenna density and road density. The cross deviation asan impotant quality parameter for the trajectories could be predicted with an accuracy of better than 40 m.


Ketersediaan
B.20160708312526.1 HAN tTersedia
Informasi Detail
Judul Seri
-
No. Panggil
526.1 HAN t
Penerbit
London : Springer., 2015
Deskripsi Fisik
viii, 178 hlm. : illus. ; 29 cm.
Bahasa
Indonesia
ISBN/ISSN
978-3-319-10828-5
Klasifikasi
526.1
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
-
Subjek
Geodesi
Info Detail Spesifik
-
Pernyataan Tanggungjawab
-
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • THE 1ST INTERNATIONAL WORKSHOP ON THE QUALITY OF GEODETIC OBSERVATION AND MONITORING SYSTEM (QUGOMS 11)
Komentar

Anda harus masuk sebelum memberikan komentar

PERPUSTAKAAN BIG
  • Informasi
  • Layanan
  • Pustakawan
  • Area Anggota

Tentang Kami

Perpustakaan Badan Informasi Geospasial (BIG) adalah sebuah perpustakaan yang berada di bawah Badan Informasi Geospasial Indonesia. Perpustakaan ini memiliki koleksi yang berkaitan dengan informasi geospasial, termasuk peta, data geospasial, dan literatur terkait. Selengkapnya

Cari

masukkan satu atau lebih kata kunci dari judul, pengarang, atau subjek

Donasi untuk SLiMS Kontribusi untuk SLiMS?

© 2025 — Senayan Developer Community

Ditenagai oleh SLiMS
Pilih subjek yang menarik bagi Anda
  • Batas Wilayah
  • Ekologi
  • Fotogrametri
  • Geografi
  • Geologi
  • GIS
  • Ilmu Tanah
  • Kartografi
  • Manajemen Bencana
  • Oceanografi
  • Penginderaan Jauh
  • Peta
Icons made by Freepik from www.flaticon.com
Pencarian Spesifik