Rebecca Gedda1,*, Larisa Beilina2, Ruomu Tan3
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1737-1759, 2023, DOI:10.32604/cmes.2022.019764
Abstract Change point detection becomes increasingly important because it can support data analysis by providing labels to the data in an unsupervised manner. In the context of process data analytics, change points in the time series of process variables may have an important indication about the process operation. For example, in a batch process, the change points can correspond to the operations and phases defined by the batch recipe. Hence identifying change points can assist labelling the time series data. Various unsupervised algorithms have been developed for change point detection, including the optimisation approach which minimises a cost function with certain… More >
Graphic Abstract
Login
Register
