Title :
Reasoning with probabilistic inputs
Author :
Yager, Ronald R. ; Filev, Dimitar P.
Author_Institution :
Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA
Abstract :
We suggest a new approach for reasoning in fuzzy models that have probabilistic inputs. It utilizes a belief structure interpretation of the probabilistic signal. We obtained result that is computationally effective and can be useful in the applications of fuzzy systems in a noisy environment
Keywords :
fuzzy systems; inference mechanisms; probability; uncertainty handling; belief structure interpretation; fuzzy models; fuzzy systems; noisy environment; probabilistic inputs; reasoning; Bismuth; Density measurement; Educational institutions; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Histograms; Machine intelligence; Probability density function; Working environment noise;
Conference_Titel :
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2125-1
DOI :
10.1109/IJCF.1994.375062
