|Author:||Sankar K. Pal,Andrej Skowron|
|Publisher:||Springer; 1 edition (June 15, 1999)|
|Category:||Technologies and Computers|
|Other formats:||doc mbr lrf txt|
Sankar K. Pal, Andrzej Skowron, Lech Polkowski.
См. также: Искусственный интелект. Sankar K. The book is devoted to the new topic: rough-neuro comp. т 15971.
Rough Fuzzy Hybridization book. Goodreads helps you keep track of books you want to read. Start by marking Rough Fuzzy Hybridization: A New Trend in Decision Making as Want to Read: Want to Read saving. Start by marking Rough Fuzzy Hybridization: A New Trend in Decision Making as Want to Read: Want to Read savin. ant to Read.
Rough-fuzzy hybridization: A new trend in decision making. Springer-Verlag, 1999. Boolean reasoning for decision rules generation. International Symposium on Methodologies for Intelligent Systems, 295-305, 1993. Rough mereology: A new paradigm for approximate reasoning. L Polkowski, A Skowron. International Journal of Approximate Reasoning 15 (4), 333-365, 1996. Pal, Rough-fuzzy knowledge encoding and uncertainty analysis: relevance in data mining, Proceedings of the 9th international conference on Distributed computing and networking, January 05-08, 2008, Kolkata, India. Rough-Fuzzy Hybridization: A New Trend in Decision Making. Anna Gomolińska, A fuzzy view on rough satisfiability, Proceedings of the 7th international conference on Rough sets and current trends in computing, June 28-30, 2010, Warsaw, Poland.
e. Rough Fuzzy Hybridization: New Trend in Decision Making, pp. 275–300. Swiniarski, . Skowron, . Independent component analysis, principal component analysis and rough sets in face recognition. Springer, Singapore (1999)Google Scholar. Transactions on Rough Sets I, 392–404 (2004)zbMATHGoogle Scholar.
Rough fuzzy hybridization is a method of hybrid intelligent system or soft computing . Pal, Andrzej Skowron.
Rough fuzzy hybridization is a method of hybrid intelligent system or soft computing, where Fuzzy set theory is used for linguistic representation of patterns, leading to a fuzzy granulation of the feature space. Rough set theory is used to obtain dependency rules which model informative regions in the granulated feature space.
Rough Fuzzy Hybridization: A New Trend in Decision Making. by Sankar K. Pal and Andrej Skowron. New Trends in Constraints: Joint ERCIM/Compulog Net Workshop Paphos, Cyprus, October 25-27, 1999 Selected Papers (Lecture Notes in Computer Science). by Krzysztof R. Apt and Antonis Kakas. New Trends in Databases and Information Systems: ADBIS 2017 Short Papers and Workshops, AMSD, BigNovelTI, DAS, SW4CH, DC, Nicosia, Cyprus, September 24–27,. in Computer and Information Science). by Mārīte Kirikova and Kjetil Nørvåg.
conflict logic with degrees, Rough Fuzzy Hybridization-A new trend in decision-making. In particular, we provide several novel algorithms in decision making problems by combining these kinds of hybrid models. Frege and . akamura: conflict logic with degrees, Rough Fuzzy Hybridization-A new trend in decision-making, (. Pal, . kowron,eds,),Springer 1999,136-150. It may be served as a foundation for developing more complicated soft set models in decision making. Probabilistic decision making based on rough sets in interval-valued fuzzy information systems.
This book bridges the gap that has developed between theory and practice. Rough Fuzzy Hybridization: A New Trend in Decision-making Sankar K. Pal,Andrzej Skowron Otenäkymä - 1999. The authors explain what fuzzy sets are, why they work, when they should be used (and when they shouldn't), and how to design systems using them. The authors take an unusual top-down approach to the design of detailed algorithms. They begin with illustrative examples, explain the fundamental theory and design methodologies, and then present more advanced case studies dealing with practical tasks. Kaikki Kirjat-palvelun tulokset Tietoja kirjailijasta (1998).
8541 RUR. Rough Fuzzy Hybridization: A New Trend in Decision-Making. Pal, A. Skowron, Sankar K. 10888 RUR. Neural Networks and Systolic Array Design. David Zhang, Sankar K. Pal. 7641 RUR. Foundations of Soft Case-Based Reasoning (Wiley Series on Intelligent Systems). Simon Shiu, Sankar K. 6435 RUR. Case–Based Reasoning in Knowledge Discovery and Data Mining. 5192 RUR. Neuro–Fuzzy Pattern Recognition. 5468 RUR.