Volume: 12, Issue: 6(2002)
pp. 435-446 DOI: 10.1142/S012906570200131X
|
|
Abstract |
Full Text (PDF, 269KB)
|
 |
| Title: |
DECISION MAKING USING HYBRID ROUGH SETS AND NEURAL NETWORKS |
| Author(s): |
YASSER HASSAN
Department of Control and System Engineering,
Toin University of Yokohama, 1614 Kurogane-cho, Aoba-ku,
Yokohama 225-8502, JapanEIICHIRO TAZAKI
Department of Control and System Engineering,
Toin University of Yokohama, 1614 Kurogane-cho, Aoba-ku,
Yokohama 225-8502, JapanSHIN EGAWA
Department of Urology, Kitasato University,
School of Medicine, 1-15-1 Kitasato Sagamihara, Kanagawa
228-8555, JapanKAZUHO SUYAMA
Department of Urology, Kitasato University,
School of Medicine, 1-15-1 Kitasato Sagamihara,
Kanagawa 228-8555, Japan
|
| History: |
Received 9 April 2002
Revised 20 September 2002
Accepted 20 September 2002
|
| Abstract: |
A methodology for using rough sets theory for preference modeling in
decision problem is presented in this paper. We will introduce a new
method where neural network systems and rough sets theory are
completely integrated into a hybrid system and are used cooperatively
for decision and classification support. At the first glance, the two
methods we discuss have not much in common. But, in spite of the
differences between them, it is interesting to try to incorporate both
into one combined system, and apply it in the building of a decision
support system. |
| Keywords: |
Rough sets; neural networks; structure adaptation; diagnostic system
|
|
|
