Review
Version 1
Preserved in Portico This version is not peer-reviewed
Advances in Machine Learning for Monitoring, Control, and Optimization of Temperature of Reactors
Version 1
: Received: 18 September 2023 / Approved: 19 September 2023 / Online: 20 September 2023 (08:59:34 CEST)
How to cite: Ahmad, I. Advances in Machine Learning for Monitoring, Control, and Optimization of Temperature of Reactors. Preprints 2023, 2023091318. https://doi.org/10.20944/preprints202309.1318.v1 Ahmad, I. Advances in Machine Learning for Monitoring, Control, and Optimization of Temperature of Reactors. Preprints 2023, 2023091318. https://doi.org/10.20944/preprints202309.1318.v1
Abstract
Machine Learning (ML) has brought about a transformative era in reactor operations, reshaping monitoring, control, and optimization strategies. This survey comprehensively explores the diverse spectrum of ML applications in industrial reactors. From real-time sensor analysis ensuring reactor functionality to adaptive control algorithms ensuring stability, ML's impact is profound and multifaceted. The benefits of ML are equally evident in optimization, encompassing performance trend prediction, proactive maintenance, and fine-tuning of operations for enhanced efficiency. This review identifies dominant ML techniques, operations stages receptive to ML integration, core data sources, and critical input-output parameters. Aimed at both academics and practitioners, this exploration enriches reactor technologies, unlocking their full potential through insights driven by ML.
Keywords
reactor operations; Machine Learning (ML); optimization; Artificial Neural Networks (ANNs); Genetic Algorithms (GAs)
Subject
Engineering, Chemical Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment