What is Time-Series Forecasting?

Time-Series Forecasting

Time-series forecasting uses historical sequential data — sensor readings, energy use, demand — to predict future values. In industry it underpins energy and demand forecasting, predictive maintenance and production planning by projecting how a measured quantity will evolve.

By learning patterns, trends and seasonality in time-stamped data, forecasting models project what comes next and flag when reality diverges. Industrial uses include forecasting energy demand for cost and grid management, predicting equipment degradation toward failure, and planning production and inventory. Accuracy depends on data quality and how stable the underlying patterns are, so forecasts are paired with monitoring for drift.