Adaptive soft sensor modeling of chemical processes based on an improved just‐in‐time learning and random mapping partial least squares
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DOI: 10.1002/cem.3554
Abstract: The just‐in‐time learning‐based partial least squares (JIT‐PLS) has been extensively applied to adaptive soft sensor modeling of complex nonlinear processes. However, it still has the problems of unreasonable relevant samples selection and unsatisfactory local modeling.… read more here.
Keywords: time learning; least squares; random mapping; partial least ... See more keywords