Quantum computation techniques for gauging reliability of interval and fuzzy data

Author

Longpré, Luc ; Servin, Christian

Author_Institution

Dept. of Comput. Sci., Univ. of Texas at El Paso, El Paso, TX

fYear

2008

Firstpage

1

Lastpage

6

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.

Keywords

computational complexity; fuzzy set theory; quantum computing; NP-hard problem; fuzzy data; interval data; quantum computation techniques; Computer science; Floods; Information resources; Instruments; Manufacturing; Measurement errors; Probability; Quantum computing; Reliability engineering; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 2008. NAFIPS 2008. Annual Meeting of the North American

Conference_Location

New York City, NY

Print_ISBN

978-1-4244-2351-4

Electronic_ISBN

978-1-4244-2352-1

Type

conf

DOI

10.1109/NAFIPS.2008.4531328

Filename

4531328