Increasing demands for on-line monitoring and control of industrial processes and their
associated variables, and the limitations of the available measuring systems have led to the …

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 …

Recent data-driven soft sensors often use multiple adaptive mechanisms to cope with non-
stationary environments. These mechanisms are usually deployed in a prescribed order …

Soft Sensors (SSs) are inferential dynamical models employed in industries to perform
prediction of process hard-to-measure variables based on their relation with easily …

Refinery industrial processes are very complex with nonlinear dynamics resulting from
varying feedstock characteristics and also from changes in product prioritization. Along …

Soft sensors are vital for online predictions of quality-related yet difficult-to-measure
variables in process industry. In this paper, an adaptive soft sensing approach based on …

The measurement of batch quality indicators in real time operation is plagued with many
challenges, hence soft sensing has become a promising solution within industrial research …

The design and application of Soft Sensors (SSs) in the process industry is a growing
research field, which needs to mediate problems of model accuracy with data availability …

building. This research reviews the use of this technique as an adaptive soft sensor building
method. It investigates different model structures, addresses issues associated with this …

One of the challenges of utilizing soft sensors is that their prediction accuracy deteriorates
with time due to multiple factors, including changes in operating conditions. Once soft …