Machine Learning Algorithms and Optimization in the Digital Transition (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 April 2025 | Viewed by 444
Special Issue Editors
2. RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Interests: machine learning; artificial intelligence; computer vision; data mining
Special Issues, Collections and Topics in MDPI journals
2. Research Centre in Asset Management and Systems Engineering, RCM2+ Lusófona University, CampoGrande, 376, 1749-024 Lisboa, Portugal
Interests: production optimization; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
2. RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Interests: machine learning; artificial intelligence; computer vision; NLP; statistics
Special Issue Information
Dear Colleagues,
To optimize and manage modern industrial systems as well as facilities, many factors must be taken into account. Modern technologies in all sectors of activity depend on large amounts of sensors and data that facilitate multivariable analyses via algorithms to support decision making in the short, middle, and long terms. Classical and deep learning machine models have boosted the capacity to analyze large volumes of data and extract patterns that greatly contribute to informed decisions, making intelligent systems more prevalent and an important part of all organizations.
Industries and large institutions are always concerned about adjusting capacity and minimizing costs, in order to meet demand without delays or the excessive use of resources. This drives research focusing on models that can provide consistent support in decision-making processes. Prediction techniques based on time series models and artificial intelligence are being used more frequently to meet these challenges and contribute to more informed decisions.
This Special Issue aims to cover the latest research so decisions made based on the proposed algorithms are sound and adequate and contribute to facilitate management as well as operational decisions. Original contributions on the above aspects, and related topics, are encouraged.
Dr. Mateus Mendes
Guest Editor
Dr. Balduíno Mateus
Dr. Nuno Lavado
Guest Editor Assistant
Manuscript Submission Information
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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.
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Keywords
- asset management
- clustering
- data analysis
- data mining
- decision-support systems
- deep learning
- fault detection
- knowledge-based systems
- machine learning
- object detection
- optimization
- predictive maintenance
- time series
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