Dynamic System Modelling from Data: Emerging Algorithms and Applications: 2nd Edition
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 527
Special Issue Editors
Interests: dynamic system modeling; identification; control; simulation
Special Issues, Collections and Topics in MDPI journals
Interests: processing control; system identification
Special Issues, Collections and Topics in MDPI journals
Interests: system identification; system modeling; artificial intelligence; deep learning; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Identification techniques for modelling from data, rather than from physical and chemical principles, usually include data processing, model structure detection, model parameter estimation, and post-validation. With fast-changing technology and ever-increasing computing capacity, many emerging algorithms in the fields of machine learning, big data, soft-sensor techniques, and reinforcement learning can realistically find applications in the identification of modern systems, ranging from manmade (engineering) to natural domains. On the other hand, no matter whatever algorithm is considered, some inherent issues must be overcome in one way or another, such as the proper handling of data uncertainty due to imperfect measurements that result in the presence of noise, time-delays, and data losses. Hence, one of the current challenges in this field is the development of identification algorithms that could yield compact mathematical models which would be useful for providing simple solutions to complex problems within a rigorous analytical framework.
The aim of this Special Issue is to report emerging novel identification algorithms for system modelling from data. The Editors welcome submissions in the form of regular technical reports, comprehensive surveys, and case studies.
Specific topics of interest include the following:
- Novel identification algorithms for systems with time-delays.
- Recent developments of machine learning algorithms and neural networks.
- Modelling, analysis, and intelligent control of dynamic systems.
- Algorithms with enhanced knowledge for intelligent automation.
- Large-scale systems: structure detection/construction and parameter estimation.
- Networked control system identification.
- Neuro-fuzzy and other inductive algorithms in theory and/or applications.
Prof. Dr. Quanmin Zhu
Prof. Dr. Jing Chen
Dr. Ya Gu
Guest Editors
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. Algorithms 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 1800 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.
Keywords
- dynamic system modelling
- data-driven identification
- intelligent algorithms
- applications
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