首页|Researchers at Baylor University Have Reported New Data on Machine Learning (Mon itoring Covariance In Multivariate Time Series: Comparing Machine Learning and Statistical Approaches)
Researchers at Baylor University Have Reported New Data on Machine Learning (Mon itoring Covariance In Multivariate Time Series: Comparing Machine Learning and Statistical Approaches)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing have been published. According to newsoriginating from Waco, Texas, by News Rx correspondents, research stated, “In complex systems withmultiple variables monitored at high-frequency, variables are not only temporally autocorrelated, b ut theymay also be nonlinearly related or exhibit nonstationarity as the inputs or operation changes. One approachto handling such variables is to detrend the m prior to monitoring and then apply control charts that assumeindependence and stationarity to the residuals.”Financial supporters for this research include United States Department of Energ y (DOE), NationalScience Foundation PFI:BIC, National Science Foundation Engine ering Research Center program, NationalAlliance for Water Innovation (NAWI) - U .S. Department of Energy, Energy Efficiency, and RenewableEnergy Office, Advanc ed Manufacturing Office.
WacoTexasUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningBaylor University
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