Fuzzy logic classification of seismic events

Author

Cercone, James A.

Author_Institution

Dept. of Electr. Eng., West Virginia Inst. of Technol., Montgomery, WV, USA

fYear

1993

fDate

7-9 Mar 1993

Firstpage

388

Lastpage

391

Abstract

Two different methods that incorporate fuzzy logic are examined for the classification of seismic events from time-series data. Linguistic descriptors incorporate characteristics such as energy content, clutter, and bursts along with well developed heuristic rules as part of a classification scheme. A direct approach involves preprocessing the waveforms and applying the parametric data to a fuzzy associative memory. In the case of direct application, the test database was capable of 100% training of three event classes from a single seismic station

Keywords

clutter; content-addressable storage; feature extraction; fuzzy logic; heuristic programming; learning (artificial intelligence); pattern classification; seismic waves; seismology; time series; waveform analysis; bursts; clutter; energy content; fuzzy associative memory; fuzzy logic; heuristic rules; preprocessing; seismic event classification; time-series data; training; Associative memory; Databases; Earthquakes; Engines; Event detection; Fuzzy logic; Fuzzy sets; Programming profession; Testing; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, 1993. Proceedings SSST '93., Twenty-Fifth Southeastern Symposium on

Conference_Location

Tuscaloosa, AL

ISSN

0094-2898

Print_ISBN

0-8186-3560-6

Type

conf

DOI

10.1109/SSST.1993.522808

Filename

522808