首页|Research Conducted at U.S.Geological Survey (USGS) Has Provided New Information about Machine Learning (Mlaapde:a Machine Learning Dataset for Determining Glo bal Earthquake Source Parameters)
Research Conducted at U.S.Geological Survey (USGS) Has Provided New Information about Machine Learning (Mlaapde:a Machine Learning Dataset for Determining Glo bal Earthquake Source Parameters)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report.According to news reporting from Golden,Colorado,by NewsRx journalists,research stated,"The Machine Learning Asset Aggregatio n of the Preliminary Determination of Epicenters (MLAAPDE) dataset is a labeled waveform archive designed to enable rapid development of machine learning (ML) m odels used in seismic monitoring operations.MLAAPDE consists of more than 5.1 m illion recordings of 120 s long three-component broadband waveform data (raw cou nts) for P,Pn,Pg,S,Sn,and Sg arrivals." The news correspondents obtained a quote from the research from U.S.Geological Survey (USGS),"The labeled catalog is collected from the U.S.Geological Survey National Earthquake Information Center's (NEIC) Preliminary Determination of Ep icenters bulletin,which includes local to teleseismic observations for earthqua kes similar to M 2.5 and larger.Each arrival in the labeled dataset has been ma nually reviewed by NEIC staff.An accompanying Python module enables users to de velop customized training datasets,which includes different time series lengths,distance ranges,sampling rates,and/or phase lists.MLAAPDE is distinct from other publicly available datasets in containing local (14%),region al (36%),and teleseismic (50%) observations,in which local,regional,and teleseismic distance are 0 degrees-3 degrees,3 degrees-30 degrees,and 30 degrees+,respectively.A recent version of the dataset is publ icly available (see Data and Resources),and user-specific versions can be gener ated locally with the accompanying software."
GoldenColoradoUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningU.S.Geolo gical Survey (USGS)
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