Deep Learning for Predictive Modeling in Large-Scale Systems
A special issue of Machine Learning and Knowledge Extraction (ISSN 2504-4990).
Deadline for manuscript submissions: closed (30 September 2023)
Special Issue Editors
Interests: machine learning; big data analytics; computational intelligence; natural computing; cyber physical systems; reliability
Interests: deep learning; computer vision
Interests: expert systems; aggregation operators; reliability & maintenance analysis; computational intelligence; multi-criteria decision making problems; optimization techniques; nature inspired algorithms; intuitionistic fuzzy set theory
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue solicits high-quality articles in the broad domain of predictive modeling using deep learning approaches. Topics of interest include but are not limited to:
(a) Anomaly Detection;
(b) Cyber–physical Systems;
(c) Time-Series Analysis;
(d) Cybersecurity;
(e) Reliability Engineering;
(f) Adversarial Learning;
(g) Explainable Models;
(h) Natural Language Processing;
(i) High-performance Computing.
The papers submitted should be sufficiently technical in nature and contain references to recent literature that has extended the state of the art. Incomplete submissions will be returned without review.
Dr. Saptarshi Sengupta
Dr. Swalpa Kumar Roy
Dr. Harish Garg
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. Machine Learning and Knowledge Extraction is an international peer-reviewed open access quarterly 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.
