Hybrid Modeling of Chemical Processes: Theory and Applications
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 207
Special Issue Editor
Interests: process analytics; process systems engineering; fault detection, diagnosis and prognosis; industrial data science; chemometrics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Industry has relied on modeling techniques for process monitoring, control, diagnosis, optimization, and design, especially since the third industrial revolution and the emergence of systems engineering. The fourth industrial revolution brought massive digitization, making it possible to collect and process large volumes of data. As a result, we are witnessing an explosion of data-driven (DD) frameworks for knowledge extraction, predictive modeling, causal explanation and diagnosis, fault detection, etc. However, one should not (must not!) leave behind all the successful solutions developed over decades based on first principles modeling (FPM) and mechanistic understanding of the systems. Both industry and researchers realize the need for new ways to integrate process and phenomenological knowledge with big data and machine learning frameworks, leading to more robust and intelligible artificial intelligence solutions, capable of assisting the target stakeholders in their activities and decision processes.
The main focus of this Special Issue is to collect state-of-the-art methods and new exciting applications of hybrid modeling (i.e., integrating DD and FPM) for monitoring, forecasting, control and optimization, especially in industrial applications. Topics include, but are not limited to:
- New hybrid model architectures;
- Platforms for hybrid modeling;
- Parameter identification for hybrid modeling;
- Physics-informed neural networks (PINNs);
- Dealing with heterogeneous knowledge and data sources;
- Hybrid control theory, approaches, and applications;
- Fault diagnosis and process health monitoring;
- Condition-based monitoring;
- Optimization, scheduling, decision making, and simulation;
- Transfer learning.
The deadline for manuscript submission is 30th June 2023.
Dr. Marco S. Reis
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
