Final Remarks

  • Robert K. Nowicki
Part of the Studies in Computational Intelligence book series (SCI, volume 802)


Since the first publications in which Professor Pawlak proposed the theory of the rough sets Pawlak (Inf Syst 6:205–218, 1981) [22]), Pawlak (Int J Comput Inf Sci 11:341–356, 1982 [23]), Pawlak (Rough Sets: Theoretical Aspects of Reasoning About Data, Kluwer, Dordrecht, 1991 [24]), many extensions and modifications of this concept have been put forward Pal and Skowron (Rough-Fuzzy Hybridization: A New Trend in Decision Making. Springer, Berlin, Heidelberg, 1999 [20]), Pawlak (Inf Sci 177:28–40, 2007 [25]), Peters et al. (Design of rough neurons: rough set foundation and petri net model. Springer, Heidelberg 2010 [29]) including the covering rough sets Zhu and Wang (Inf Sci 152:217–230, 2003 [36]), Zhu and Wang (A new type of covering rough set, 444–449, 2006 [37]), Zhu and Wang (IEEE Trans Knowl Data Eng 19:1131–1144, 2007 [38]), the rough neural networks Lingras (Rough neural networks, 1445–1450, 1996 [13]), Peters et al. (Design of rough neurons: rough set foundation and petri net model. Springer, Berlin, Heidelberg, pp. 283–291, 2010 [27]), the variable precision rough sets Ziarko (J. Comput Syst Sci 46:39–59, 1993 [39]), the multicriteria rough decision systems Greco (INFOR Inf Syst Oper Res 38:161–195, 2000[7]) and many others.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Computational IntelligenceCzstochowa University of TechnologyCzstochowaPoland

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