title: Decision making using hybrid rough sets and neural networks.
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.
authors.affiliation: 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
authors.forename: Yasser
authors.initials: Y
authors.lastname: Hassan
authors.forename: Eiichiro
authors.initials: E
authors.lastname: Tazaki
authors.forename: Shin
authors.initials: S
authors.lastname: Egawa
authors.forename: Kazuho
authors.initials: K
authors.lastname: Suyama
mesh_terms: 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
chemical_list: D017430:Prostate-Specific Antigen