Event Identification - Applications to Area of Interest Events

Sax, Robert L.; Bell, A.G.R.; Dietz, Donald L; Strauss, A.C.; Shaub, Jeffrey S

doi:10.21236/ada072956

Cited by 3 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The views and conclusions presented are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the Advanced Research Projects Agency, the Air Force Technical Applications Center, or the US Government. ENSCO, INC. vii Sax, et al (1978) was used to classify, as an earthquake or an explosion, each of 12 8 events drawn from an Area of Interest (AI) data base (the Priority II data set). The specific goals of the study were:…”

Section: Discussionmentioning

confidence: 99%

“…1-5 cluster model would be required to identify explosions from the two areas. Sax, et al (1978) developed an adaptive discrimination model as an answer to the issues raised by Sax (1976). The initial approach in the 19 78 study was to assume that a single cluster could adequately represent earthquakes, but that multiple clusters would be needed to represent explosions.…”

Section: Ensco Incmentioning

confidence: 99%

“…The initial approach in the 19 78 study was to assume that a single cluster could adequately represent earthquakes, but that multiple clusters would be needed to represent explosions. This strategy was successfully demonstrated by Sax, et al (1978) using data for 35 central Asian events which were recorded at 22 world-wide stations. However, the same concept, when applied to the data for the 12 8 events analyzed in this report, produced unsatisfactory results.…”

Section: Ensco Incmentioning

confidence: 99%

See 2 more Smart Citations

Event Identification Experiment: Priority II Data Set

Sax¹,

Bell²,

Dietz³

1979

View full text Add to dashboard Cite

«CCUWITY CLASSIFICATION OF THIS ^AOEfWun Data Bnffd) 19. (continued) Network measurements Adaptive identification 20. (continued) '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 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 .<» By correcting one of these problems-magnitude scaling-and oy re-running the data base, the same classification performance was\ obtained with only one earthquake cluster. This showed the importance of identifying and eliminating such operational problems. "Qur final results indicated that all of the explosions could be detected as members of a single cluster. However, 141 of the earthquakes remained unidentified and 4% were falsely identified as explosions. This evaluation neglects two explosions both of whiöh were incorrectly edited. Additional work is needed to improve identification of earthquakes by means of multidiscriminant analysis. UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGEfWh«! Dal« Enltrtd)

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Ensco Incmentioning

confidence: 99%

Section: Ensco Incmentioning

confidence: 99%

See 1 more Smart Citation

Event Identification Experiment: Priority II Data Set

Sax¹,

Bell²,

Dietz³

1979

View full text Add to dashboard Cite

show abstract

“…Table C-3 defines the raw signal measurements present in the data record. The amplitude measurements (words are corrected for distance using appropriate B-factors (Sax et al, 1978).…”

Section: Ens '-Incmentioning

confidence: 99%