Title :
Knowledge representation and approximate reasoning with Type II fuzzy sets
Author_Institution :
Dept. of Ind. Eng., Toronto Univ., Ont.
Abstract :
Type II fuzzy sets are considered with the perspective of fuzzy normal forms for fuzzy knowledge representation and inference. In this perspective all of the classical laws are reinterpreted to hold as “a matter of degree”. A particular version of Type II fuzzy sets are the interval-valued fuzzy sets. Furthermore, when knowledge is represented with the interval-valued Type II fuzzy sets, fuzzy reasoning generates consequences that are interval-valued Type II fuzzy sets. A new non-specificity measure helps us assess the uncertainty content associated with interval valued Type II fuzzy sets
Keywords :
fuzzy logic; fuzzy set theory; inference mechanisms; knowledge representation; uncertainty handling; Type II fuzzy sets; approximate reasoning; fuzzy reasoning; inference; interval-valued fuzzy sets; knowledge representation; uncertainty handling; Fuzzy logic; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Industrial engineering; Knowledge representation; Measurement uncertainty;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.409941