Recognition of anomalies from time series by fuzzy logic methods

J. Zlotnicki
Observatoire de Physique du Globe, Clermont-Ferrand, France

J.  Bonnin
L'Institut de Physique du Globe de Strasbourg, Strasbourg, France

Abstract

[1]  This paper is devoted to the detection of anomalies by the fuzzy comparison algorithm for recognition of signals (FCARS). The algorithm is a result of soft (based on fuzzy mathematics) modeling of interpreter's logic and continues in this direction the difference recognition algorithm for signals (DRAS) and the fuzzy logic algorithm for recognition of signals (FLARS), previously developed by the authors. A characteristic feature of FCARS is a more comprehensive use of the so-called fuzzy comparisons introduced by the authors. This makes FCARS more versatile and adaptive than DRAS and FLARS.

Received 20 December 2007; accepted 28 December 2007; published 24 January 2008.

Keywords: fuzzy logic, anomaly, rectification, recognition.

Index Terms: 8419 Volcanology: Volcano monitoring; 8494 Volcanology: Instruments and techniques; 9805 General or Miscellaneous: Instruments useful in three or more fields.

Citation: Gvishiani, A. D., S. M. Agayan, Sh. R. Bogoutdinov, E. M. Graeva, J. Zlotnicki, and J.  Bonnin (2008), Recognition of anomalies from time series by fuzzy logic methods, Russ. J. Earth Sci., 10, ES1001, doi:10.2205/2007ES000278.