Abstract Machine learning and artificial intelligence techniques have an ever-increasing
presence and impact on a wide-variety of research and commercial fields. Disappointed by …

Soft sensors for regression applications (SSR) are inferential models that use online
available sensors (eg temperature, pressure, flow rate, etc.) to predict quality variables …

In the last two decades Soft Sensors established themselves as a valuable alternative to the
traditional means for the acquisition of critical process variables, process monitoring and …

This new edition of the bestselling Measurement, Instrumentation, and Sensors Handbook
brings together all aspects of the design and implementation of measurement …

In this article, we review and discuss algorithms for adaptive data-driven soft sensing. In
order to be able to provide a comprehensive overview of the adaptation techniques …

The nonlinear time-varying characteristics of the process industry can be modeled using
numerous data-driven soft sensor methods. However, the intrinsic relationships among the …

We are living in an era of rapidly develo** technology. Dynamic systems control is not a
new methodology, but it is heavily influenced by the development of technologies for …

We present results for the" Impact Project Focus Area" on the topic of symbolic execution as
used in software testing. Symbolic execution is a program analysis technique introduced in …

The digital twins concept enhances modeling and simulation through the integration of real-
time data and feedback. This review elucidates the foundational elements of digital twins …

In many industrial plants, development and implementation of advanced monitoring and
control techniques require real-time measurement of process quality variables. However, on …