@inproceedings{7505a11b101b4461bf9c174237509ff1,
title = "A probabilistic rough set approach for water reservoirs site location decision making",
abstract = "Recently, advanced methods have been developed for selection of suitable sites for water reservoirs. Although these methods being developed and some new approaches, like GIS techniques, are being used currently, all these methods are mostly dependent on engineering decision making and a need for high cost. In this study, a new approach in the determination of water reservoirs location is proposed. The core of the proposed approach is a soft hybrid induction system called the Generalized Distribution Table and Rough Set System (GDT-RS) to discover classification rules. The system is based on a combination of Generalized Distribution Table (GDT) and the Rough Set methodologies the proposed approach is applied for water reservoirs site location and the results indicate that it is very effective and accurate.",
keywords = "Decision making, Generalized Distribution Table (GDT), Rough set theory, water reservoirs",
author = "Shaaban, \{Shaaban M.\} and Nabwey, \{Hossam A.\}",
year = "2012",
doi = "10.1007/978-3-642-31075-1\_27",
language = "English",
isbn = "9783642310744",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "358--372",
booktitle = "Computational Science and Its Applications - 12th International Conference, ICCSA 2012, Proceedings",
edition = "PART 2",
note = "12th International Conference on Computational Science and Its Applications, ICCSA 2012 ; Conference date: 18-06-2012 Through 21-06-2012",
}