首页|Patent Issued for Determining component contributions of timeseries model (USPT O 12159240)
Patent Issued for Determining component contributions of timeseries model (USPT O 12159240)
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The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Time-series data contains sequential data point s (e.g., data values) that are observedat successive time durations (e.g., hour ly, daily, weekly, monthly, annually, etc.). For example, monthlyrainfall, dail y stock prices, annual profits, etc., are examples of time-series data. Forecast ing is a machinelearning process which can be used to observe historical values of time-series data and predict future valuesof the time-series data. There ar e numerous types of forecasting models including exponential smoothingwhich use s a weighted sum of past observations of the time-series to make predictions abo ut future valuesof the data.
NETL
NSTL
