Seismic Pattern Recognition.

Abstract

The paper applies various pattern recognition techniques to the problem of discriminating underground nuclear explosion seismic signals from those of natural earthquakes. The data set consists of 186 short period seismograms recorded by the Large Aperture Seismic Array in Montana. Enough seismic and pattern recognition theory is developed to allow easy interpretation of the results. The techniques tested run the gamut from simple, linear classifiers to a complex, adaptive, nonlinear classifier. The best results were 99.4% correct identification of earthquakes and 94.2% correct identification of explosions. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1972
Accession Number
AD0757877

Entities

People

  • Ronald D. Bouvier

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Arrays
  • Data Sets
  • Earthquakes
  • Explosions
  • Identification
  • Machine Learning
  • Nuclear Explosions
  • Pattern Recognition
  • Recognition
  • Seismic Arrays

Readers

  • Neural Network Machine Learning.
  • Seismology
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference