eCite Digital Repository

Fuzzy more isn't not less; it is not much less

Citation

Malhotra, V, Fuzzy more isn't not less; it is not much less, Proceedings of the 2001 International Joint Conference on Neural Networks, 15-19 July 2001, Washington, DC, pp. 1340-1344. ISBN 0-7803-7046-5 (2001) [Refereed Conference Paper]

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. In this paper, 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.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Virtual Reality and Related Simulation
Objective Division:Information and Communication Services
Objective Group:Other Information and Communication Services
Objective Field:Information and Communication Services not elsewhere classified
Author:Malhotra, V (Dr Vishv Malhotra)
ID Code:23558
Year Published:2001
Deposited By:Computing
Deposited On:2001-08-01
Last Modified:2017-04-07
Downloads:0

Repository Staff Only: item control page