Spatio-Temporal Prediction (STP) node

Spatio-Temporal Prediction (STP) has many potential applications such as energy management for buildings or facilities, performance analysis and forecasting for mechanical service engineers, or public transport planning. In these applications, measurements such as energy usage are often taken over space and time. Questions that might be relevant to the recording of these measurements include what factors will affect future observations, what can be done to effect a wanted change, or to better manage the system? To address these questions, you can use statistical techniques that can forecast future values at different locations, and can explicitly model adjustable factors to perform what-if analysis.

STP analysis uses data that contains location information, input fields for prediction (predictors), a time field, and a target field. Each location has numerous rows in the data that represent the values of each predictor at each time of measurement. After the data is analyzed, you can use it to predict target values at any location within the shape data that is used in the analysis. It can also forecast when input data for the future points in time are known.