FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3166998418> ?p ?o ?g. }

• W3166998418 abstract "&lt;p&gt;At Stromboli, minor volcanic eruptions occur at time intervals of approximately five minutes on average, making it one of the most active volcanoes worldwide. In addition to these mostly harmless events, there are also stronger eruptions and paroxysms which pose a serious threat to residents and tourists. In light of recent developments in Machine Learning, this study attempts to apply these new tools for the analysis of the time-varying volcanic eruptions at Stromboli. As input for the Machine-Learning approach, we use continuous recordings of seismic signals from two seismometers on the island. The data is available from IRIS &amp;#160;and includes records starting in 2012 up to the present.&amp;#160;&lt;/p&gt;&lt;p&gt;One primary challenge is to label and classify the data, i.e., to discriminate events of interest from noise. The variety of signal-appearance in the recorded data is wide, in some periods the events are clearly distinguishable from noise whereas, in other cases relevant events are obscured by the high noise level. To enable the event-detection in all cases, we developed the following algorithm: in the first step, the seismic data is pre-processed with an STA/LTA-Filter, which allows detection of events based on a prominence threshold. However, due to the diversity of signal patterns, a fixed set of hyperparameters (STA- and LTA-window length, prominence threshold, correlation coefficient) fails to reliably extract the relevant events in a consistent manner. Therefore, the (time-varying) noise level of the recordings is used as an additional key indicator. After this, the hyperparameters are optimized. The automatic adaptation is then used for labeling the continuous seismic data.&lt;/p&gt;&lt;p&gt;After extracting the events based on this approach, a machine learning model is trained to analyze the recordings for possible patterns in the interval times and the event amplitudes. This study is expected to provide constraints on the possibility to detect complex time-dependent patterns of the eruption history at Stromboli.&lt;/p&gt;" @default.
• W3166998418 created "2021-06-22" @default.
• W3166998418 creator A5000432967 @default.
• W3166998418 creator A5010223871 @default.
• W3166998418 creator A5019657676 @default.
• W3166998418 creator A5027999474 @default.
• W3166998418 creator A5035515939 @default.
• W3166998418 creator A5055956023 @default.
• W3166998418 creator A5072711194 @default.
• W3166998418 creator A5085065741 @default.
• W3166998418 creator A5090727444 @default.
• W3166998418 date "2021-04-18" @default.
• W3166998418 modified "2023-10-16" @default.
• W3166998418 title "Machine Learning analysis of seismic signals recorded at Stromboli Volcano" @default.
• W3166998418 doi "https://doi.org/10.5194/egusphere-egu21-13166" @default.
• W3166998418 hasPublicationYear "2021" @default.
• W3166998418 type Work @default.
• W3166998418 sameAs 3166998418 @default.
• W3166998418 citedByCount "0" @default.
• W3166998418 crossrefType "posted-content" @default.
• W3166998418 hasAuthorship W3166998418A5000432967 @default.
• W3166998418 hasAuthorship W3166998418A5010223871 @default.
• W3166998418 hasAuthorship W3166998418A5019657676 @default.
• W3166998418 hasAuthorship W3166998418A5027999474 @default.
• W3166998418 hasAuthorship W3166998418A5035515939 @default.
• W3166998418 hasAuthorship W3166998418A5055956023 @default.
• W3166998418 hasAuthorship W3166998418A5072711194 @default.
• W3166998418 hasAuthorship W3166998418A5085065741 @default.
• W3166998418 hasAuthorship W3166998418A5090727444 @default.
• W3166998418 hasConcept C106131492 @default.
• W3166998418 hasConcept C115961682 @default.
• W3166998418 hasConcept C119217923 @default.
• W3166998418 hasConcept C119857082 @default.
• W3166998418 hasConcept C120806208 @default.
• W3166998418 hasConcept C121332964 @default.
• W3166998418 hasConcept C127313418 @default.
• W3166998418 hasConcept C154945302 @default.
• W3166998418 hasConcept C165205528 @default.
• W3166998418 hasConcept C2779662365 @default.
• W3166998418 hasConcept C31972630 @default.
• W3166998418 hasConcept C41008148 @default.
• W3166998418 hasConcept C62520636 @default.
• W3166998418 hasConcept C99498987 @default.
• W3166998418 hasConceptScore W3166998418C106131492 @default.
• W3166998418 hasConceptScore W3166998418C115961682 @default.
• W3166998418 hasConceptScore W3166998418C119217923 @default.
• W3166998418 hasConceptScore W3166998418C119857082 @default.
• W3166998418 hasConceptScore W3166998418C120806208 @default.
• W3166998418 hasConceptScore W3166998418C121332964 @default.
• W3166998418 hasConceptScore W3166998418C127313418 @default.
• W3166998418 hasConceptScore W3166998418C154945302 @default.
• W3166998418 hasConceptScore W3166998418C165205528 @default.
• W3166998418 hasConceptScore W3166998418C2779662365 @default.
• W3166998418 hasConceptScore W3166998418C31972630 @default.
• W3166998418 hasConceptScore W3166998418C41008148 @default.
• W3166998418 hasConceptScore W3166998418C62520636 @default.
• W3166998418 hasConceptScore W3166998418C99498987 @default.
• W3166998418 hasLocation W31669984181 @default.
• W3166998418 hasOpenAccess W3166998418 @default.
• W3166998418 hasPrimaryLocation W31669984181 @default.
• W3166998418 hasRelatedWork W1537641342 @default.
• W3166998418 hasRelatedWork W19523314 @default.
• W3166998418 hasRelatedWork W199628537 @default.
• W3166998418 hasRelatedWork W2089519317 @default.
• W3166998418 hasRelatedWork W2105097891 @default.
• W3166998418 hasRelatedWork W2320611907 @default.
• W3166998418 hasRelatedWork W2598834849 @default.
• W3166998418 hasRelatedWork W4253374395 @default.
• W3166998418 hasRelatedWork W4296826616 @default.
• W3166998418 hasRelatedWork W4321489916 @default.
• W3166998418 isParatext "false" @default.
• W3166998418 isRetracted "false" @default.
• W3166998418 magId "3166998418" @default.
• W3166998418 workType "article" @default.