We consider a clustering-based construction of a soft sensor with adaptive model structure
and parameters and with the time factor taken into account by the example of an industrial …

The problem of adaptive soft sensor development with the use of clustering methods is
considered in the examples of a reactive distillation process for the production of methyl tert …

When adaptive soft sensors are introduced to industrial plants, an appropriate combination
of the type of adaptation mechanism, hyperparameters of the mechanism, regression model …

The problem of developing an adaptive soft sensor (SS) using clustering methods is
considered to be an example of an industrial reactive distillation process for the production …

The paper improves the existing methods of developing nonlinear soft sensors via a
nonparametric approach based on the example of industrial distillation unit. The proposed …

Soft sensor technology is an important means to estimate important process variables in real-
time. Modeling for soft sensor system is the core of this technology. Most nonlinear dynamic …

Since in practical industrial applications, soft sensors based on static models often lead to
low accuracy and poor robustness, a multiple neural network (MNN) model is presented to …

In the paper a soft sensor design strategy for an industrial process, via neural NMA model, is
described. A general design strategy, based on the automatic selection of regressors of a …

The advancement of method of nonlinear soft sensor development using a nonparametric
approach based on the example of industrial multicomponent distillation column is …

In process industries, there is a great demand for additional process information such as the
product quality level or the exact process state estimation. At the same time, there is a large …