Data cleaning in the process industries

S Xu, B Lu, M Baldea, TF Edgar, W Wojsznis… - Reviews in Chemical …, 2015 - degruyter.com
In the past decades, process engineers are facing increasingly more data analytics
challenges and having difficulties obtaining valuable information from a wealth of process …

Advances and opportunities in machine learning for process data analytics

SJ Qin, LH Chiang - Computers & Chemical Engineering, 2019 - Elsevier
In this paper we introduce the current thrust of development in machine learning and
artificial intelligence, fueled by advances in statistical learning theory over the last 20 years …

Neural-network contributions in biotechnology

G Montague, J Morris - Trends in biotechnology, 1994 - cell.com
System modelling and identification are fundamental to bioprocess engineering, where it is
often necessary to approximate a real system with an appropriate model, given a set of input …

Data-driven soft sensor development based on deep learning technique

C Shang, F Yang, D Huang, W Lyu - Journal of Process Control, 2014 - Elsevier
In industrial process control, some product qualities and key variables are always difficult to
measure online due to technical or economic limitations. As an effective solution, data …

Process data analytics in the era of big data

SJ Qin - AIChE Journal, 2014 - scholars.ln.edu.hk
For engineering systems where processes, units, and equipment are designed with clear
objectives and are usually operated under well‐controlled circumstances as designed …

Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing

J Wang, J Xie, R Zhao, L Zhang, L Duan - Robotics and computer …, 2017 - Elsevier
Pervasiveness of ubiquitous computing advances the manufacturing scheme into a
ubiquitous manufacturing era which poses significant challenges on sensing technology …

Soft sensors for product quality monitoring in debutanizer distillation columns

L Fortuna, S Graziani, MG Xibilia - Control Engineering Practice, 2005 - Elsevier
The paper deals with the design of neural based soft sensors to improve product quality
monitoring and control in a refinery by estimating the stabilized gasoline concentration (C5) …

[图书][B] Learning automata: theory and applications

K Najim, AS Poznyak - 2014 - books.google.com
Learning systems have made a significant impact on all areas of engineering problems.
They are attractive methods for solving many problems which are too complex, highly non …

[HTML][HTML] Digitization in bioprocessing: The role of soft sensors in monitoring and control of downstream processing for production of biotherapeutic products

AS Rathore, S Nikita, NG Jesubalan - Biosensors and Bioelectronics: X, 2022 - Elsevier
Owing to the advancement in the technologies, the vision of smart manufacturing is not
implausible. Development of sophisticated measuring tools, modelling approaches …

A SIA-LSTM based virtual metrology for quality variables in irregular sampled time sequence of industrial processes

X Yuan, Z Jia, L Li, K Wang, L Ye, Y Wang… - Chemical Engineering …, 2022 - Elsevier
In industrial processes, there are usually strongly dynamic temporal relationship between
process data sequence. Hence, dynamic modeling methods are popular for soft sensing of …