Overview
Industrial Artificial Intelligence is a peer-reviewed, open access journal that highlights the development of AI techniques in improving industrial processes.
- Publishes research on AI techniques that optimize solutions to modern industrial practices.
- Advocates real-world industrial applications, addressing issues in industrial data modelling, control, and optimization.
- Promotes advanced machine learning techniques for industrial process intelligent sensing and industrial data modelling.
- Main Editor
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- Dianhui Wang,
- Witold Pedrycz,
- Tianyou Chai
- Submission to first decision (median)
- 28 days
- Downloads
- 11,657 (2023)
Latest articles
Journal updates
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Special Issue Proposal Guidelines
Review our SI guidelines and proposal requirements in this section.
Journal information
- Electronic ISSN
- 2731-667X
- Abstracted and indexed in
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- Baidu
- CLOCKSS
- CNKI
- CNPIEC
- DBLP
- DOAJ
- Dimensions
- EBSCO
- Google Scholar
- INSPEC
- Naver
- OCLC WorldCat Discovery Service
- Portico
- ProQuest
- TD Net Discovery Service
- Wanfang
- Copyright information