Advanced Machine Learning Techniques, Applications and Developments
A special issue of Applied System Innovation (ISSN 2571-5577).
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 26582
Special Issue Editors
2. INESC TEC, 4200-465 Porto, Portugal
Interests: statistical modelling; forecasting; optimization; machine learning
Special Issues, Collections and Topics in MDPI journals
2. INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal
Interests: time series forecasting; machine learning; deep learning; data science; big data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Industries are heavily investing in new digital technologies such as AI, machine learning, and big data analysis, aiming for higher efficiency and new business opportunities. AI is expected to radically change the way companies operate and generate value. For example, in the manufacturing industry, AI creates many opportunities for companies, such as preventive and predictive maintenance, identification of defects in the manufacturing process, demand and forecasting tools, and inventory planning. They hold promise as drivers of some of the most influential research in the twenty-first century since they generate innovation in a wide range of research fields, encompassing such diverse areas as healthcare, logistics and distribution, manufacturing industries, business technology, transportation, energy, environmental issues, etc. The disciplines are inherently multidisciplinary, involving mathematics, physics, and computing.
Against this backdrop, this Special Issue calls for a more critical discussion and outlook for the real-world applications in AI and machine learning and the latest progress in utilizing these groundbreaking technologies, and aims to share gained insights. We invite authors to contribute original research articles addressing significant issues and contributing towards the development of new concepts, methodologies, applications, trends, and knowledge in science. Review articles describing the current state of the art are also welcome.
Prof. Dr. Patrícia Ramos
Prof. Dr. José Oliveira
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. Applied System Innovation is an international peer-reviewed open access semimonthly 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 1400 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.
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