5 edition of **Rough sets, fuzzy sets, data mining and granular computing** found in the catalog.

- 306 Want to read
- 18 Currently reading

Published
**2009**
by Springer in Berlin, New York
.

Written in English

- Soft computing,
- Data Mining,
- Fuzzy sets,
- Congresses,
- Computer science,
- Data mining,
- Granular Computing,
- Fuzzy-Menge,
- Grobmenge

**Edition Notes**

Statement | Hiroshi Sakai ... [et al. (eds.). |

Series | Lecture notes in artificial intelligence, subseries of lecture notes in computer science -- 5908, Lecture notes in computer science -- 5908., Lecture notes in computer science |

Contributions | Sakai, Hiroshi |

Classifications | |
---|---|

LC Classifications | QA75.5 .R494 2009 |

The Physical Object | |

Pagination | xiii, 528 p. : |

Number of Pages | 528 |

ID Numbers | |

Open Library | OL25000801M |

ISBN 10 | 3642106455 |

ISBN 10 | 9783642106453 |

LC Control Number | 2009940136 |

OCLC/WorldCa | 471802650 |

Data Mining, Rough Sets and Granular Computing. based on the existing feature selection method by using a fuzzy rough set-based information entropy, a corresponding fast algorithm is provided. Peters J, Feng H and Ramanna S Adaptive granular control of an HVDC system Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, () Gomolińska A () A Comparative Study of Some Generalized Rough Approximations, Fundamenta Informaticae, , (), Online publication.

Skowron A and Peters J Rough sets Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, () Pal S Rough-Fuzzy granular computing, case based reasoning and data mining Proceedings of the 5th international conference on Fuzzy Logic and Applications, (). Get this from a library! Rough sets, fuzzy sets, data mining and granular computing: 11th international conference, RSFDGrC , Toronto, Canada, May , proceedings. [Aijun An;].

Lee "Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 15th International Conference, RSFDGrC , Tianjin, China, November , , Proceedings" por disponible en Rakuten Kobo. This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Brand: Springer International Publishing. Read "Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 15th International Conference, RSFDGrC , Tianjin, China, November , , Proceedings" by available from Rakuten Kobo. This book constitutes the refereed conference proceedings of the 15th International Conference on Rough SBrand: Springer International Publishing.

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This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrCheld in Tianjin, China in November as one of the co-located conference of the Joint Rough Set Symposium Manufacturer: Springer.

Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 11th International Conference, RSFDGrC Toronto, Canada, MayProceedings (Lecture Notes in Computer Science ()) [An, Aijun, Pedrycz, Witold, Stefanowski, Jerzy, Ramanna, Sheela, Butz, Cory J.] on *FREE* shipping on qualifying offers.

Rough Sets, Fuzzy Sets, Data Mining and Granular Computing Format: Paperback. This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCheld in Delhi, India in December in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI This volume contains the papers selected for presentation at the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC ) held at Chongqing University of Posts and Telecommunications, Chongqing.

RSFDGrC was?rst - ganized as the 7th International Workshop on Rough Sets, Data Mining and Granular Computing held in Yamaguchi, Japan in Its key feature was to stress the role of integrating intelligent information methods to solve real-world, large, complex problems concerned with uncertainty and fuzziness.

This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCorganized at the University of Regina, August 31st–September 3rd, This conference followed in the footsteps of inter.

This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCfuzzy sets at the University of Regina, August 31st–September 3rd, This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCheld in Moscow, Russia in June The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83 submissions.

The rough sets not only can be used to deal with new uncertain information systems, but also can optimize many existing soft computing methods. For the rough set theory, in the process of data mining, there are still a large number of problems need to be discussed, such as large data sets, efficient reduction algorithm, parallel computing Cited by: This volume contains the papers selected for presentation at the 11th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC ), a part of the Joint Rough Set Symposium (JRS ) organized by Infobright Inc.

and York University. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 9th International Conference, RSFDGrC Chongqing, China, MayProceedings (Lecture Notes in Computer Science ()) [Wang, Guoyin, Liu, Qing, Skowron, Andrzej, Yao, Yiyu] on *FREE* shipping on qualifying offers.

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 9th International Format: Paperback. In computer science, a rough set, first described by Polish computer scientist Zdzisław I. Pawlak, is a formal approximation of a crisp set (i.e., conventional set) in terms of a pair of sets which give the lower and the upper approximation of the original set.

In the standard version of rough set theory (Pawlak ), the lower- and upper-approximation sets are crisp sets, but in other. ´ ˛zak Sergei O. Kuznetsov Dominik Sle Daryl H. Hepting Boris G.

Mirkin (Eds.) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing 13th International Conference, RSFDGrC Moscow. This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrCheld in Halifax, Canada in October as one of the co-located conference of the Joint Rough Set Symposium, JRS Skowron A and Peters J Rough sets Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, () Save to Binder Create a New Binder.

This book constitutes the refereed proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCheld in Toronto, Canada in May in conjunction with the Second International Conference on Rough Sets and Knowledge Technology, RSKTboth as part of the Joint Rough Set Symposium, JRS Author: Aijun An.

Rough fuzzy sets and fuzzy rough sets. In order to cope with categorical and numerical data in datasets, fuzzy rough set theory Bridging gaps between several forms of granular computing.

Rough Sets, Fuzzy Sets, Data Mining and Granular Computing Book January with Reads How we measure 'reads' A 'read' is counted each. deﬁned and represented as a (fuzzy) set, and the granular str ucture is a family of (fuzzy) sets.

Additional studies of granular computing, within the context of computational intelligence, can be found in recently edited books,22,39,51 a book by Bargiela and Pedrycz,4 and conferences proceedings of International Conference on Rough Sets.

Granular Computing Based Data Mining in the Views of Rough Set and Fuzzy Set: /ch Granular computing (GrC) is a label of theories, methodologies, techniques, and tools that make use of granules in the process of problem solving.

TheCited by:. Lecture Notes in Computer Science > Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing > Data Mining > Rough set reverse method enables prediction of the best values for condition attributes given values for the decision attributes.granular computing and rough sets 3 groups, which led to the proof that the degree 5 polynomial is insolvable by radical, and etc.

[3]), in theoretical computer science (the divide-and-conquer.This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrCorganized at the University of Regina, August 31st&#;September 3rd, This conference followed in the footsteps of Brand: Dominik Slezak.