Autor: Gnat, M. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Spatial database modeling for indoor navigation systems
Autorzy:: Gotlib, D.
Gnat, M.
Powiązania:: https://bibliotekanauki.pl/articles/106828.pdf
Data publikacji:: 2013
Wydawca:: Politechnika Warszawska. Wydział Geodezji i Kartografii
Tematy:: geoinformatyka
kartografia
modelowanie budowy
nawigacja domowa
GIS
BIM
geoinformatics
cartography
building modeling
indoor navigation
Opis:: For many years, cartographers are involved in designing GIS and navigation systems. Most GIS applications use the outdoor data. Increasingly, similar applications are used inside buildings. Therefore it is important to find the proper model of indoor spatial database. The development of indoor navigation systems should utilize advanced teleinformation, geoinformatics, geodetic and cartographical knowledge. The authors present the fundamental requirements for the indoor data model for navigation purposes. Presenting some of the solutions adopted in the world they emphasize that navigation applications require specific data to present the navigation routes in the right way. There is presented original solution for indoor data model created by authors on the basis of BISDM model. Its purpose is to expand the opportunities for use in indoor navigation.
Źródło:: Reports on Geodesy and Geoinformatics; 2013, 95; 49-63
2391-8365
2391-8152
Pojawia się w:: Reports on Geodesy and Geoinformatics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Artificial neural networks and fuzzy inference systems for line simplification with extended WEA metric
Autorzy:: Olszewski, R.
Gnat, M.
Fiedukowicz, A.
Powiązania:: https://bibliotekanauki.pl/articles/145362.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: informacja geograficzna
kartografia
sieci neuronowe
generalization of geographic information
line simplification
computational intelligence
ANN
FIS
Opis:: The issue of line simplification is one of the fundamental problems of generalisation of geographical information, and the proper parameterisation of simplification algorithms is essential for the correctness and cartographic quality of the results. The authors of this study have attempted to apply computational intelligence methods in order to create a cartographic knowledge base that would allow for non-standard parameterisation of WEA (Weighted Effective Area) simplification algorithm. The aim of the conducted research was to obtain two independent methods of non-linear weighting of multi-dimensional regression function that determines the “importance” of specific points on the line and their comparison to each other. The first proposed approach consisted in the preparation of a set of cartographically correct examples constituting a basis for teaching a neural network, while the other one consisted in defining inference rules using fuzzy logic. The obtained results demonstrate that both methods have great potential, although the proposed solutions require detailed parameterisation taking into account the specificity of geometric variety of the source data.
Źródło:: Geodesy and Cartography; 2018, 67, 2; 255-269
2080-6736
2300-2581
Pojawia się w:: Geodesy and Cartography
Dostawca treści:: Biblioteka Nauki

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