Event Identification Experiment: Priority II Data Set

Abstract

Using multidiscriminant analysis, events from a data base of 128 seismic events are identified as either earthquakes or explosions. Each event was observed by means of a network of 24 seismic stations. Discriminants derived from short-period and long-period measurements were then used to classify the events. The discriminants were based on spectral shape and on time domain measurements of event complexity. An empirical 'cluster analysis' procedure was used to associate a given event with events having similar discriminant patterns. By training on known earthquakes, eight clusters were required to separate earthquakes into groups into with similar discriminant patterns. Only one cluster was needed to classify explosions. These results are adaptive, in that no prior knowledge of explosion discriminant patterns were required to obtain these results. Several operational problems were identified by cluster analysis.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 10, 1979
Accession Number
ADA956071

Entities

People

  • Alan G. Bell
  • Donald L. Dietz
  • Robert L. Sax

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Bandpass Filters
  • Bandwidth
  • Computations
  • Data Sets
  • Databases
  • Detection
  • Detectors
  • False Alarms
  • Frequency Bands
  • Identification Systems
  • Maximum Likelihood Estimation
  • Quality Control
  • Scattering
  • Surface Waves
  • United States

Readers

  • Computational Modeling and Simulation
  • Seismology