"Clustering"

Assessment of unsupervised standard pattern recognition methods for industrial energy time series

Finding and extracting standard patterns in energy time series is very important to many real-world applications. Hence, there exists a multitude of pattern recognition algorithms with a majority of them being supervised ones. The advantage of …

Demand response clustering — automatically finding optimal cluster hyper-parameter values

Time series clustering methods, such as Fuzzy C-Means (FCM) noise clustering, can be efficiently used to obtain typical price-influenced load profiles (TPILPs) through the data-driven analysis and modelling of the consumption behaviour of household …