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A neural network approach to seismic phase identification

Technical Report ·
OSTI ID:6772741

An automatic phase identification system that employs a neural network approach to classifying seismic event phases is described. Extraction of feature vectors used to distinguish the different classes is explained, and the design and training of the neural networks in the system are detailed. Criteria used to evaluate the performance of the neural network approach are provided.

Research Organization:
Sandia National Labs., Albuquerque, NM (United States)
Sponsoring Organization:
DOE; USDOE, Washington, DC (United States)
DOE Contract Number:
AC04-76DP00789
OSTI ID:
6772741
Report Number(s):
SAND-92-1185; ON: DE93013601
Country of Publication:
United States
Language:
English

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Related Subjects

58 GEOSCIENCES
580000* -- Geosciences
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
ARTIFICIAL INTELLIGENCE
CLASSIFICATION
COMPUTER ARCHITECTURE
DATA ACQUISITION
DATA PROCESSING
DETECTION
EARTHQUAKES
EXPERT SYSTEMS
FORECASTING
FOURIER TRANSFORMATION
INTEGRAL TRANSFORMATIONS
NEURAL NETWORKS
PROCESSING
SEISMIC EVENTS
TRANSFORMATIONS