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The use of rough rules in the selection of topographic objects for generalizing geographical information


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Adamiak N., 1979, Logika. Warszawa: Wydawnictwo Uniwersytetu Warszawskiego.Search in Google Scholar

Beaubouef T., Petry F.E., 2010, Fuzzy and rough set approaches for uncertainty in spatial data. Berlin – Heidelberg: Springer, pp. 103–129.10.1007/978-3-642-14755-5_5Search in Google Scholar

Browne, M.W., 2000, Cross-validation methods. “Journal of Mathematical Psychology” Vol. 44, no. 1, pp. 108–132.10.1006/jmps.1999.1279Search in Google Scholar

Cornelis C., Martín G.H., Jensen R., Ślȩzak D., 2008, Feature selection with fuzzy decision reducts. In: Proceedings of the International Conference on Rough Sets and Knowledge Technology, Chengdu, China, 17–18 May 2008, Berlin – Heidelberg: Springer, pp. 284–291.10.1007/978-3-540-79721-0_41Search in Google Scholar

Dubois D., Prade H., 1990, Rough fuzzy sets and fuzzy rough sets. “Intern. Journal of General Systems” Vol, 17, no. 2/3, pp. 191–209.10.1080/03081079008935107Search in Google Scholar

Fawcett T., 2006, An introduction to ROC analysis. “Pattern Recognition Letters” Vol. 27, no. 8, pp. 861–874.10.1016/j.patrec.2005.10.010Search in Google Scholar

Fiedukowicz A., 2013a, Construction of fuzzy interference system for generalization of geographic information – selection of roads segments. In: “Geo-informatica Polonica” Vol. 12, pp. 53–62.10.2478/v10300-012-0013-2Search in Google Scholar

Fiedukowicz A., 2013b, Wykorzystanie zbiorów przybliżonych do pozyskiwania wiedzy i budowy reguł systemu generalizacji informacji geograficznej. „Roczniki Geomatyki” T. 11, nr 2(59), pp. 33–46.Search in Google Scholar

Fiedukowicz A., 2015a, Fuzzy rough sets theory reducts for quantitative decisions – Approach for spatial data generalization. In: Pattern Recognition and Machine Intelligence. Proceedings. Eds. M. Kryszkiewicz end al. „Lecture Notes in Computer Science” Vol. 9124, pp. 314–323.10.1007/978-3-319-19941-2_30Search in Google Scholar

Fiedukowicz A., 2015b, Redukcja wymiarowości problemu – ograniczenie liczby cech. In: Wybrane metody eksploracyjnej analizy danych przestrzennych (Spatial Data Mining). Eds. A. Fiedukowicz, J. Gąsiorowski, R. Olszewski. Warszawa: Wydział Geodezji i Kartografii Politechniki Warszawskiej.Search in Google Scholar

Fiedukowicz A., 2017, Metodyka wykorzystania reduktów i reguł przybliżonych w procesie generalizacji informacji geograficznej. PhD. dissertation, Warsaw University of Technology, Faculty of Geodesy and Cartography.Search in Google Scholar

Fiedukowicz A., 2020, The role of spatial context information in the generalization of geographic information: Using reducts to indicate relevant attributes. “ISPRS International Journal of Geo-Information” Vol. 9, no. 1, 37.10.3390/ijgi9010037Search in Google Scholar

Greco S., Matarazzo B., Słowiński R., 2001, Rough sets theory for multicriteria decision analysis. “European Journal of Operational Research” Vol. 129, pp. 1–47.10.1016/S0377-2217(00)00167-3Search in Google Scholar

Harrie L., Weibel R., 2007, Modelling the overall process of generalization. In: Generalization of Geographic Information. Amsterdam: Elsevier Science BV, pp. 67–87.10.1016/B978-008045374-3/50006-5Search in Google Scholar

Łukasiewicz J., 1958, Elementy logiki matematycznej. Warszawa: Państwowe Wydawnictwo Naukowe.Search in Google Scholar

Olszewski R., 2009, Kartograficzne modelowanie rzeźby terenu metodami inteligencji obliczeniowej. “Prace Naukowe Politechniki Warszawskiej. Geodezja” No. 46.Search in Google Scholar

Pawlak Z., 1982, Rough sets. “Intern. Journal of Comput. Information Science” Vol. 11, no. 5, pp. 341–356.10.1007/BF01001956Search in Google Scholar

Pawlak Z., 1991, Rough sets: Theoretical aspects of reasoning about data. Dordrecht: Kluwer Academic Publishing.Search in Google Scholar

Pawlak Z., Grzymala-Busse J., Słowiński R., Ziarko W., 1995, Rough sets. “Communication of the ACM” Vol. 38, pp. 88–95.10.1145/219717.219791Search in Google Scholar

Regnauld N., McMaster R.B., 2007, A synoptic view of generalization operators. In: Generalisation of Geographic Information. Amsterdam: Elsevier Science BV, pp. 37–66.10.1016/B978-008045374-3/50005-3Search in Google Scholar

Roth R.E., Brewer C.A., Stryker M.S., 2011, A typology of operators for maintaining legible map designs at multiple scales. “Cartographic Perspective” Vol. 68, pp. 29–64.10.14714/CP68.7Search in Google Scholar

Shea K.S., McMaster R.B., 1989, Cartographic generalization in a digital environment: When and how to generalize. In: Proceedings of the Auto-Carto, Baltimore, MD, USA, Vol. 9, pp. 56–67.Search in Google Scholar

Słowiński R., Greco S., Matarazzo B., 2014, Rough-set-based decision support. In: Search Methodologies. Boston MA, pp. 557–609.10.1007/978-1-4614-6940-7_19Search in Google Scholar

Zadeh L. A., 1965, Fuzzy sets. “Information and Control” Vol. 8, no. 3, pp. 338–353.10.1016/S0019-9958(65)90241-XSearch in Google Scholar

Zhang J., 2001, Using rough set represent the uncertainty in GIS spatial data. In: Proceedings of ICA Conference Beijing, China.Search in Google Scholar

eISSN:
2450-6966
ISSN:
0324-8321
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Geosciences, Cartography and Photogrammetry, other, History, Topics in History, History of Science