Soft sensors are mathematical models employed to estimate hard-to-measure variables from
available easy-to-measure variables. These sensors are typically developed using either …

Nano biochemical sensors play an important role in detecting the biomarkers related to
human diseases, and carbon nanotubes (CNTs) have become an important factor in …

Increasing data-driven soft sensors have been adopted to online predict the quality indices
in polymerization processes to improve the availability of measurements and efficiency …

Most applications of soft sensors in process industries require learning from a stream of
data, which may exhibit nonstationary dynamics, or concept drift. In this study, we develop a …

Heavy metal pollution remains a major concern for the public today, in line with the growing
population and global industrialization. Heavy metal ion (HMI) is a threat to human and …

The goal of this paper is to design and implementation of a new data-driven soft sensor that
uses state dependent parameter (SDP) models to improve product quality monitoring. The …

RNA-cleaving DNAzyme is a very useful biomaterial for metal ions determination. However,
parts of DNAzymes can be cleaved by several metal ions, which makes it difficult to …

This work addresses recent developments for solving problems in process systems
engineering based on machine learning algorithms. A general description of most popular …

This paper presents the development of hybrid machine learning models to forecast the
natural flows of water bodies. Five models were considered under the analysis: extreme …

The catalytic hydrogenation of carbon dioxide (CO 2) to methanol presents a significant
opportunity for both mitigating climate change and producing a valuable chemical feedstock …