Quantum Computations Techniques for Gauging Reliability of Interval and Fuzzy Data

Authors

Luc Longpre, The University of Texas at El PasoFollow
Christian Servin, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow

Publication Date

7-2009

Comments

Technical Report: UTEP-CS-08-08c

Short version published in Proceedings of the 27th International Conference of the North American Fuzzy Information Processing Society NAFIPS'2008, New York, New York, May 19-22, 2008; full paper to appear in International Journal of General Systems, 2011, Vol. 40, No. 1

Abstract

In traditional interval computations, we assume that the interval data corresponds to guaranteed interval bounds, and that fuzzy estimates provided by experts are correct. In practice, measuring instruments are not 100% reliable, and experts are not 100% reliable, we may have estimates which are "way off", intervals which do not contain the actual values at all. Usually, we know the percentage of such outlier un-reliable measurements. However, it is desirable to check that the reliability of the actual data is indeed within the given percentage. The problem of checking (gauging) this reliability is, in general, NP-hard; in reasonable cases, there exist feasible algorithms for solving this problem. In this paper, we show that quantum computations techniques can drastically speed up the computation of reliability of given data.