A segmentation based similarity measure for time series data

Abstract

Focusing on the objectives of Demand Side Management (DSM), we propose a novel time series distance metric that better capture the information related to similar peaks/off-peaks. The proposed metric uses autocorrelation based segmentation and similar segment identification for computation of overall distance. Experiment shows the proposed distance advances the state-of-the-art.