Computational modeling toward full chain of polypropylene production: From molecular to industrial scale
Since polypropylene was synthesized in 1954, tremendous breakthroughs have been
achieved in transferring polypropylene from a discovery in the laboratory to an …
achieved in transferring polypropylene from a discovery in the laboratory to an …
Ensemble deep kernel learning with application to quality prediction in industrial polymerization processes
For predicting the melt index (MI) in industrial polymerization processes, traditional data-
driven empirical models do not utilize the information in a large amount of the unlabeled …
driven empirical models do not utilize the information in a large amount of the unlabeled …
Applications of support vector machines in chemistry
O Ivanciuc - Reviews in computational chemistry, 2007 - Wiley Online Library
Kernel-based techniques (such as support vector machines, Bayes point machines, kernel
principal component analysis, and Gaussian processes) represent a major development in …
principal component analysis, and Gaussian processes) represent a major development in …
Performance prediction and analysis of a PEM fuel cell operating on pure oxygen using data-driven models: A comparison of artificial neural network and support …
IS Han, CB Chung - International Journal of Hydrogen Energy, 2016 - Elsevier
Two data-driven models are presented to predict and analyze the performance of a PEM fuel
cell operating on pure oxygen that can be used as an effective power source for air …
cell operating on pure oxygen that can be used as an effective power source for air …
Data-Driven Modeling Based on Two-Stream Gated Recurrent Unit Network With Soft Sensor Application
R Xie, K Hao, B Huang, L Chen… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Data-driven soft sensors, estimating the pivotal quality variables, have been widely
employed in industrial process. This paper proposes a novel soft sensor modeling approach …
employed in industrial process. This paper proposes a novel soft sensor modeling approach …
Integrated soft sensor using just-in-time support vector regression and probabilistic analysis for quality prediction of multi-grade processes
Multi-grade processes have played an important role in the fine chemical and polymer
industries. An integrated nonlinear soft sensor modeling method is proposed for online …
industries. An integrated nonlinear soft sensor modeling method is proposed for online …
[HTML][HTML] Developing spectrotransfer functions (STFs) to predict basic physical and chemical properties of calcareous soils
Spectroscopy in visible (Vis) and near-infrared (NIR) provides a rapid, timely, non-
destructive, low-preparation, and less expensive analysis of soil samples in comparison with …
destructive, low-preparation, and less expensive analysis of soil samples in comparison with …
Auto-switch Gaussian process regression-based probabilistic soft sensors for industrial multigrade processes with transitions
Prediction uncertainty has rarely been integrated into traditional soft sensors in industrial
processes. In this work, a novel autoswitch probabilistic soft sensor modeling method is …
processes. In this work, a novel autoswitch probabilistic soft sensor modeling method is …
Melt index prediction by least squares support vector machines with an adaptive mutation fruit fly optimization algorithm
W Wang, X Liu - Chemometrics and Intelligent Laboratory Systems, 2015 - Elsevier
Melt index (MI) plays an important role in determining product specification, and is
influenced by a large number of process variables in the practical manufacturing process of …
influenced by a large number of process variables in the practical manufacturing process of …
Soft chemical analyzer development using adaptive least-squares support vector regression with selective pruning and variable moving window size
Y Liu, N Hu, H Wang, P Li - Industrial & Engineering Chemistry …, 2009 - ACS Publications
Soft analyzers have been increasingly accepted as an alternative to physical ones in the
chemical industry to infer and improve the product quality. In this study, an adaptive least …
chemical industry to infer and improve the product quality. In this study, an adaptive least …