Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

With the predicted depletion of natural resources and alarming environmental issues,
sustainable development has become a popular as well as a much-needed concept in …

Process monitoring is crucial for maintaining favorable operating conditions and has
received considerable attention in previous decades. Currently, a plant-wide process …

Multi-agent systems (MASs) are typically composed of multiple smart entities with
independent sensing, communication, computing, and decision-making capabilities …

Deep learning is a recently developed feature representation technique for data with
complicated structures, which has great potential for soft sensing of industrial processes …

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 …

In recent years, multi-modal measurements of process and product properties have become
widely popular. Sometimes classical chemometric methods such as principal component …

Width deviation is an important metric for evaluating the quality of a hot-rolled strip in steel
production systems. This paper considers a width deviation prediction problem and …

Industrial process data are usually time-series data collected by sensors, which have the
characteristics of high nonlinearity, dynamics, and noises. Many existing soft sensor …

Industrial process data are usually mixed with missing data and outliers which can greatly
affect the statistical explanation abilities for traditional data-driven modeling methods. In this …