Title :
Integrated Study in Incomplete Information System
Author_Institution :
Comput. Center, Yangzhou Univ., Yangzhou, China
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;
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
DOI :
10.1109/AICI.2009.454
