Machine learning in bioprocess development: from promise to practice
Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess
development provides large amounts of heterogeneous experimental data, containing …
development provides large amounts of heterogeneous experimental data, containing …
Physics-informed machine learning modeling for predictive control using noisy data
Due to the occurrence of over-fitting at the learning phase, the modeling of chemical
processes via artificial neural networks (ANN) by using corrupted data (ie, noisy data) is an …
processes via artificial neural networks (ANN) by using corrupted data (ie, noisy data) is an …
Machine learning-based predictive control using noisy data: evaluating performance and robustness via a large-scale process simulator
Abstract Machine learning modeling of chemical processes using noisy data is a practically
challenging task due to the occurrence of overfitting during learning. In this work, we …
challenging task due to the occurrence of overfitting during learning. In this work, we …
Analyzing the occurrence of foaming in batch fermentation processes using multiway partial least square approaches
This article presents an application of multiway partial least squares (MPLS) methods to
develop interpretative correlation models to monitor the foaming occurrence and improve …
develop interpretative correlation models to monitor the foaming occurrence and improve …
Applications of Machine Learning to Optimizing Polyolefin Manufacturing
N Sharma, YA Liu - arxiv preprint arxiv:2401.09753, 2024 - arxiv.org
This chapter is a preprint from our book by, focusing on leveraging machine learning (ML) in
chemical and polyolefin manufacturing optimization. It's crafted for both novices and …
chemical and polyolefin manufacturing optimization. It's crafted for both novices and …
[KSIĄŻKA][B] Machine Learning Modeling for Process Control and Electrochemical Reactor Operation
J Luo - 2023 - search.proquest.com
Electrochemical reaction processes attract increasing attention as a promising chemical
process alternative to achieve green and sustainable chemical manufacturing due to its …
process alternative to achieve green and sustainable chemical manufacturing due to its …
Large-scale industrial fermenter foaming control: automated machine learning for antifoam prediction and defoaming process implementation
In industrial fermenters, antifoaming agents (AFA) are often added in a reactive manner to
prevent foaming in a reactor. To successfully predict the antifoam addition in a proactive …
prevent foaming in a reactor. To successfully predict the antifoam addition in a proactive …
Deep learning classification system for coconut maturity levels based on acoustic signals
The advancement of computer image processing, pattern recognition, signal processing,
and other technologies has gradually replaced the manual methods of classifying fruit with …
and other technologies has gradually replaced the manual methods of classifying fruit with …
[KSIĄŻKA][B] Process Structure-Aware Machine Learning Modeling for State Estimation and Model Predictive Control of Nonlinear Processes
M Alhajeri - 2022 - search.proquest.com
Big data is a cornerstone component of the fourth industrial revolution, which calls on
engineers and researchers to fully utilize data in order to make smart decisions and …
engineers and researchers to fully utilize data in order to make smart decisions and …
Sistema de control basado en machine learning para cultivo celular en modo fed-batch considerando datos de un modelo cinético para el metabolismo central de …
TAM Pérez Ushijima - 2024 - repositorio.uchile.cl
En los últimos años la industria a nivel global ha presentado innovación en términos de la
implementación de tecnologías basadas en la Industria 4.0., incluyendo la inteligencia …
implementación de tecnologías basadas en la Industria 4.0., incluyendo la inteligencia …