Artificial neural networks and fuzzy inference systems for line simplification with extended WEA metric

• Autorzy: Olszewski R. , Gnat M. , Fiedukowicz A.

Identyfikatory

DOI

10.24425/118708

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

generalization of geographic information; line simplification; computational intelligence; ANN; FIS

PL

informacja geograficzna; kartografia; sieci neuronowe

• Wydawca: Komitet Geodezji PAN
• Czasopismo: Geodesy and Cartography
• Rocznik: 2018
• Tom: Vol. 67, no. 2
• Strony: 255--269
• Opis fizyczny: Bibliogr. 29 poz., rys., tab., wykr.

Twórcy

autor

Olszewski R.

• Warsaw University of Technology, Faculty of Geodesy and Cartography 1 Plac Politechniki, 00-661 Warszaw, Poland

autor

Gnat M.

• Warsaw University of Technology, Faculty of Geodesy and Cartography 1 Plac Politechniki, 00-661 Warszaw, Poland

autor

Fiedukowicz A.

• Warsaw University of Technology, Faculty of Geodesy and Cartography 1 Plac Politechniki, 00-661 Warszaw, Poland

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019)