Integrated Study in Incomplete Information System

Author

Rui Zhang

Author_Institution

Comput. Center, Yangzhou Univ., Yangzhou, China

Volume

4

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

346

Lastpage

349

Abstract

Both rough set theory and D-S evidence theory are important methods in uncertainty reasoning, and each one has its own advantages and disadvantages. Incomplete information system exists widely in real life. In this paper, two theories are used in combination to study the incomplete information system. First, reduction algorithm for the incomplete information system is put forward based on rough set theory; and then D-S evidence theory is used to optimize the obtained rules, and the results were verified by example.

Keywords

case-based reasoning; information systems; rough set theory; uncertain systems; D-S evidence theory; Incomplete Information System; reduction algorithm; rough set theory; uncertainty reasoning; Artificial intelligence; Competitive intelligence; Computational intelligence; Databases; Information systems; Information technology; Intelligent systems; Learning systems; Set theory; Uncertainty; D-S Evidence Theory; Decision Table; Incomplete Information System; Reduction; Rough Set Theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.454

Filename

5376326