DocumentCode
479742
Title
Statistical Default Inference Based on DFL
Author
Zhang Min
Author_Institution
Coll. of Comput. Eng., Jimei Univ., Xiamen
Volume
1
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
172
Lastpage
175
Abstract
Statistical default logic is an expansion of classical (i.e. Reiter´s) default logic that allows us to model common inference patterns found in standard inferential statistics, which is an expansion with an error-bound parameter. This paper proposes statistical default inference based on dynamic fuzzy logic (DFL) and constructs a method of computing extensions of fuzzy statistical default theory.
Keywords
fuzzy logic; fuzzy set theory; inference mechanisms; statistical analysis; DFL; Reiter´s default logic; error-bound parameter; fuzzy statistical default theory; inference patterns; inferential statistics; statistical default inference; statistical default logic; Artificial intelligence; Computer errors; Computer science; Educational institutions; Error analysis; Fuzzy logic; Software engineering; Dynamic Fuzzy Logic; Fuzzy Statistical Default Extension; Statistical Default Inference;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.765
Filename
4721719
Link To Document