Recent Advances in Machine Learning and Applications
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Advanced Digital and Other Processes".
Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 94970
Special Issue Editor
Interests: machine learning and AI applications; process quality control and engineering optimization; machine vision and inspection
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid advancement of digital technologies of cyber-physical systems, the high-dimensionality, noise contamination, incompleteness, inconsistency, and massive amounts of data from the ubiquity of the Internet of Things (IoT) have posed significant challenges for academic and industrial applications. Artificial intelligence models based on machine learning (ML) are used in data analytics and process optimization, which play significant roles in many research directions. Since 2012, various machine learning technologies have been quick to develop and have proven to be of substantial practical value in a diversity of application domains. Such technology has solved numerous complex industrial problems that have existed in the AI community for many years, such as predictive maintenance, process optimization, task scheduling, quality improvement, supply and demand forecasting, defect detection, vibration signal recognition, and many more. Machine learning is one of the liveliest areas of discussion and is central in current process technological developments. To review recent advances in machine learning, this Special Issue on "Recent Advances in Machine Learning and Applications" will focus on publishing high-quality original research studies that address challenges in the broad area of optimization and artificial intelligence in-process applications. Topics include but are not limited to the following:
- ML models and applications for predictive maintenance, quality control, and process optimization
- ML models and applications for smart manufacturing process monitoring and control
- ML models and application for intelligent manufacturing diagnostics, prognostics, and asset health management
- ML models and applications for scheduling and supply chain management
- ML models and applications for robotics and human–machine interaction
- ML algorithms and approaches to handling big data, data imbalance, uncertainty, data fusion, etc.
Prof. Dr. Chien-Chih Wang
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.
Keywords
- Smart manufacturing process monitoring, quality control, and process optimization
- Intelligent manufacturing diagnostics, prognostics, and asset health management
- Intelligent scheduling and supply chain management
- Intelligent risk management and anomaly management detection
- Smart robotics and human–machine interaction
- Digital transformation through advances in artificial intelligence
- Case study and innovation-decision for traditional industry and small and medium enterprises
- ML algorithms and approaches to handling big data, data imbalance, uncertainty, data fusion, etc.
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.