Detecting electricity demand patterns using a new method for high-dimensional binary data

Detecting electricity demand patterns using a new method for high-dimensional binary data

Forecasting electricity demand in buildings is now more accurate with Group Encoding (GE), a new method that uses only existing device operation data. Developed by researchers at the Institute of Science Tokyo, the method improved prediction accuracy by 74% in real-world tests.