This dataset contains previously published data on induced seismicity that has been processed to be machine learning ready. The data contains time series of the cumulative number of seismic events in certain areas and the corresponding pressures induced from injecting fluids into the ground. The natural task is to forecast future seismicity given past seismicity and pressures. These datasets aim to require as little seismology experience as necessary to prepare the data for forecasting algorithms. Data is provided for different locations. For Decatur Illinois, the seismic data was taken from Williams-Stroud et al., 2018 and the pressure data originated from Luu et al., 2022. Data aggregated over the whole region lies in the temporal_data...
Datasets associated with manuscript "Cascadia Subduction Zone Fault Heterogeneities from Newly Detec...
The database and its accompanying files are as follows: GEoREST_database_Readme (.txt): provides an...
This study deals with addressing the scientific achievements and the history of earthquake predictio...
We need more investment in the new energy, but we also need to assess the impacts of the clean energ...
Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process ...
Estimating the location, time and magnitude of a possible earthquake has been the subject of many st...
The curation of seismic datasets is the cornerstone of seismological research and the starting point...
The earthquake rupture process reflects complex interactions of stress, fracture and frictional prop...
Machine learning algorithms are used in this thesis to predict earthquake parameters for simulated a...
Since 2009, the Central U.S. has been subjected to a new type of seismic hazard attributed to human ...
This article aims to discusses machine learning modelling using a dataset provided by the LANL (Los ...
Open access to curated datasets positively impacts on scientific research of machine learning and de...
This article provides an overview of current applications of machine learning (ML) in seismology. ML...
A new generation of earthquake catalogs developed through supervised machine-learning illuminates ea...
The complexity of the earthquake rupture process makes earthquakes inherently unpredictable. Seismic...
Datasets associated with manuscript "Cascadia Subduction Zone Fault Heterogeneities from Newly Detec...
The database and its accompanying files are as follows: GEoREST_database_Readme (.txt): provides an...
This study deals with addressing the scientific achievements and the history of earthquake predictio...
We need more investment in the new energy, but we also need to assess the impacts of the clean energ...
Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process ...
Estimating the location, time and magnitude of a possible earthquake has been the subject of many st...
The curation of seismic datasets is the cornerstone of seismological research and the starting point...
The earthquake rupture process reflects complex interactions of stress, fracture and frictional prop...
Machine learning algorithms are used in this thesis to predict earthquake parameters for simulated a...
Since 2009, the Central U.S. has been subjected to a new type of seismic hazard attributed to human ...
This article aims to discusses machine learning modelling using a dataset provided by the LANL (Los ...
Open access to curated datasets positively impacts on scientific research of machine learning and de...
This article provides an overview of current applications of machine learning (ML) in seismology. ML...
A new generation of earthquake catalogs developed through supervised machine-learning illuminates ea...
The complexity of the earthquake rupture process makes earthquakes inherently unpredictable. Seismic...
Datasets associated with manuscript "Cascadia Subduction Zone Fault Heterogeneities from Newly Detec...
The database and its accompanying files are as follows: GEoREST_database_Readme (.txt): provides an...
This study deals with addressing the scientific achievements and the history of earthquake predictio...