International Business Machines Corporation
FORECASTING MODEL GENERATION FOR TIME SERIES DATA WITH CHANGE POINT AND SEASONALITY

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Abstract:

A method, apparatus, system, and computer program product for creating a forecasting model for time series data. Seasonality is removed from the times series data having the seasonality and trends to form deseasoned time series data. Trend models are created for sets of candidate change points in the deseasoned time series data. The trend models are for the sets of candidate change points without the seasonality. Seasonal models are created using the time series data without the trends. The seasonal models have different time periods for the seasonality. The trend models are combined with the seasonal models to form complete models that take into account the seasonality and the trends. The forecasting model is selected from the complete models in which the forecasting model is a best fit to a set of criteria.

Status:
Application
Type:

Utility

Filling date:

21 Jan 2020

Issue date:

22 Jul 2021