Classification of uncertain data: An application in nondestructive testing
| Autor(en): | Hülsmann, J. Brockmann, W. |
Stichwörter: | Classification; Classification (of information); Classification of data; Classification performance; Classification results; Data processing; Fuzzy rule-based classifier; Knowledge based systems; Magnetic Flux Leakage; Magnetic leakage; Nondestructive examination, Information management; Nondestructive Testing; Trust Management; Uncertain datas; Uncertainty; Uncertainty, Artificial intelligence | Erscheinungsdatum: | 2012 | Journal: | Communications in Computer and Information Science | Volumen: | 299 CCIS | Ausgabe: | PART 3 | Startseite: | 231 | Seitenende: | 240 | Zusammenfassung: | The classification of data with dynamically changing uncertainty characteristics is a problem for many practical applications. As an example in the field of nondestructive testing (NDT), magnetic flux leakage (MFL) measurements are used to inspect pipelines. The data is analyzed manually afterwards. In this paper we use a framework for handling uncertainties called Trust Management and a extended fuzzy rule based classifier to identify different installations within pipelines by MFL-data. The results show a classification performance of over 90% with an additional, reliable measure for the trustworthiness of every single classification result. © 2012 Springer-Verlag Berlin Heidelberg. |
Beschreibung: | Conference of 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012 ; Conference Date: 9 July 2012 Through 13 July 2012; Conference Code:93506 |
ISBN: | 9783642317170 | ISSN: | 18650929 | DOI: | 10.1007/978-3-642-31718-7_24 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84868088439&doi=10.1007%2f978-3-642-31718-7_24&partnerID=40&md5=fa5f26eda8d839e57149b8bad9da8256 |
Show full item record
