Title :
Fuzzy more isn´t not less; It is not much less
Author_Institution :
Sch. of Comput., Tasmania Univ., Hobart, Tas., Australia
Abstract :
Fuzzy values are convenient way for representing measurements that are inherently uncertain. Clearly, two uncertain values can not be compared using the standard greater than operator-fuzziness would render many cases liable to incorrect outcomes. We develop a risk-based model to set a threshold that can be used to minimise risk exposure from incorrect outcomes in comparisons involving fuzzy values
Keywords :
fuzzy logic; uncertainty handling; fuzziness; fuzzy values; incorrect outcomes; risk exposure; risk-based model; uncertain measurements; Australia; Computer industry; Computer networks; Costs; Equations; Fuzzy neural networks; Fuzzy sets; Neural networks; Temperature; Thumb;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939556
