Understanding the timing of eruption end using a machine learning approach to classification of seismic time series
The timing and processes that govern the end of volcanic eruptions are not yet fully understood, and there currently exists no systematic definition for the end of a volcanic eruption. Currently, end of eruption is established either by generic criteria (typically 90 days after the end of visual sig...
المؤلفون الرئيسيون: | Manley, G, Pyle, D, Mather, T, Rodgers, M, Clifton, D, Stokell, BG, Thompson, G, Londoño, JM, Roman, DC |
---|---|
التنسيق: | Journal article |
اللغة: | English |
منشور في: |
Elsevier
2020
|
مواد مشابهة
-
Machine learning approaches to identifying changes in eruptive state using multi-parameter datasets from the 2006 eruption of Augustine Volcano, Alaska
حسب: Manley, G, وآخرون
منشور في: (2021) -
Long-range correlations identified in time-series of volcano seismicity during dome-forming eruptions using detrended fluctuation analysis
حسب: Lachowycz, S, وآخرون
منشور في: (2013) -
A deep active learning approach to the automatic classification of volcano-seismic events
حسب: Manley, G, وآخرون
منشور في: (2022) -
Quiescent-explosive transitions during dome-forming volcanic eruptions: Using seismicity to probe the volcanic processes leading to the 29 July 2008 Vulcanian Explosion of Soufrière Hills Volcano, Montserrat
حسب: Rodgers, M, وآخرون
منشور في: (2016) -
A statistical model for the timing of earthquakes and volcanic eruptions influenced by periodic processes
حسب: Jupp, T, وآخرون
منشور في: (2004)