[HTML][HTML] The role of artificial intelligence-driven soft sensors in advanced sustainable process industries: A critical review
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 …
sustainable development has become a popular as well as a much-needed concept in …
Review on data-driven modeling and monitoring for plant-wide industrial processes
Z Ge - Chemometrics and Intelligent Laboratory Systems, 2017 - Elsevier
Data-driven modeling and applications in plant-wide processes have recently caught much
attention in both academy and industry. This paper provides a systematic review on data …
attention in both academy and industry. This paper provides a systematic review on data …
Deep learning with spatiotemporal attention-based LSTM for industrial soft sensor model development
X Yuan, L Li, YAW Shardt, Y Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Industrial process data are naturally complex time series with high nonlinearities and
dynamics. To model nonlinear dynamic processes, a long short-term memory (LSTM) …
dynamics. To model nonlinear dynamic processes, a long short-term memory (LSTM) …
Predictors of support for biodiversity loss countermeasure and bushmeat consumption among Vietnamese urban residents
Biodiversity loss is happening at an unprecedented rate, especially in countries like
Vietnam, with rich biodiversity and a high population growth rate. One of the main causes of …
Vietnam, with rich biodiversity and a high population growth rate. One of the main causes of …
Nonlinear dynamic soft sensor modeling with supervised long short-term memory network
X Yuan, L Li, Y Wang - IEEE transactions on industrial …, 2019 - ieeexplore.ieee.org
Soft sensor has been extensively utilized in industrial processes for prediction of key quality
variables. To build an accurate virtual sensor model, it is very significant to model the …
variables. To build an accurate virtual sensor model, it is very significant to model the …
Data mining and analytics in the process industry: The role of machine learning
Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …
decision making/supports in the process industry over the past several decades. As a …
Deep learning-based feature representation and its application for soft sensor modeling with variable-wise weighted SAE
In modern industrial processes, soft sensors have played an important role for effective
process control, optimization, and monitoring. Feature representation is one of the core …
process control, optimization, and monitoring. Feature representation is one of the core …
Hierarchical quality-relevant feature representation for soft sensor modeling: A novel deep learning strategy
Deep learning is a recently developed feature representation technique for data with
complicated structures, which has great potential for soft sensing of industrial processes …
complicated structures, which has great potential for soft sensing of industrial processes …
Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data
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 …
affect the statistical explanation abilities for traditional data-driven modeling methods. In this …
A dynamic CNN for nonlinear dynamic feature learning in soft sensor modeling of industrial process data
X Yuan, S Qi, Y Wang, H Xia - Control Engineering Practice, 2020 - Elsevier
Hierarchical local nonlinear dynamic feature learning is of great importance for soft sensor
modeling in process industry. Convolutional neural network (CNN) is an excellent local …
modeling in process industry. Convolutional neural network (CNN) is an excellent local …