Decision making using hybrid rough sets and neural networks.
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.
Hassan
Yasser
Y
Department of Control and System Engineering, Toin University of Yokohama, 1614 Kurogane-cho, Aoba-ku, Yokohama 225-8502 Japan. y_fouad@intlab.toin.ac.jp
Tazaki
Eiichiro
E
Egawa
Shin
S
Suyama
Kazuho
K
D000465:Algorithms; D001706:Biopsy; D003657:Decision Making; D003661:Decision Support Techniques; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen / Q000097:blood; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000097:blood / Q000473:pathology / Q000601:surgery; D012307:Risk Factors; D016896:Treatment Outcome
D017430:Prostate-Specific Antigen