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Soft sensing applications for non-stable processes based on a weighted high-order dynamic information structure
2020
IEEE Access
Nowadays, industrial processes are fully equipped by redundant hardware sensors which can be interfered by random noises. Hence, it is of high importance to develop soft sensing solutions for key variables prediction and process monitoring. Various methods have been carried out to cope with different data characteristics among which auto-correlation and non-stable features have been considered as two challenging tasks. In this paper, a novel weighted autoregressive dynamic latent variable
doi:10.1109/access.2020.3038684
fatcat:alzjifcspnggjorfu43rtjdqci