- June 11, 2026
- Durham, N.C.
The International Society of Automation (ISA) — the leading professional society for automation — announced that its ISA Transactions journal achieved the top CiteScore in its category from Elsevier, publishers of ScienceDirect.
ScienceDirect is a full-text scientific database of articles and book chapters from more than 2,500 peer-reviewed journals and more than 11,000 books. Elsevier’s CiteScore for ISA Transactions this year is 13.9, compared to 12.3 in the previous year, and its Impact Factor is 6.5.
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. The CiteScore measures the average citations received per peer-reviewed document published in ISA Transactions. The chart below depicts the ISA Transactions Citescore for the last two years compared with other competing journals in the same/similar domain.
ISA Transactions, a bimonthly publication, publishes advances and state-of-the-art in the science and engineering of measurement and automation. It provides value to leading-edge industrial practitioners and applied researchers. Its intended audience is research and development personnel from academia and industry in the fields of control systems, process instrumentation, systems and automation.
Figure 1: CiteScore measures the average number of citations received by a journal in a single year to documents published in the previous four years. This chart depicts the ISA Transactions Citescore for the last two years compared to other competing journals in the same/similar domain.
Recent Topics Covered
Editor-in-Chief Dr. Ahmad Rad and the volunteer editors and editorial board members of ISA Transactions seek to bridge the gap between theory and practice. Automation professionals throughout the world rely on ISA Transactions for its scholarly value and quality, and for the credibility and usefulness of its peer-reviewed content.
Articles published recently on digital twins, for example, include:
- Digital twin-assisted self-supervised contrastive learning: A novel framework for electromechanical equipment fault diagnosis
- Digital twin-based fault tolerance approach for Cyber–Physical Production System
- A novel quantitative diagnosis method for rolling bearing faults based on digital twin model
- A faulty simulation model guided Ramanujan Digital twin architecture for rotating machine health monitoring
- Straddle-type monorail train gearbox fault diagnosis based on digital twin and domain adaptation
A search of recently published articles shows the range of content covered:
- Design of the GPPI controller for stability and performance of unstable plant models with long dead times, by Alejandro Rojas and Daniel Sbarbaro
- Observer-based output-feedback stabilization of nonlinear systems with periodically event-triggered sampled-output-data by Xueling Li, Min Wang and Xiangze Lin
- Adaptive distribution transformation for enhanced bearing fault detection in independent cart systems, by Abdul Jabbar, Marco Cocconcelli and Gianluca D’Elia
- Deep learning-enhanced prescribed-time cooperative guidance with switching topologies under time-varying velocity by Heng Li, Zheng Guo, Xiwang Dong
- High-resolution sound source localization via non-synchronous measurements based on symmetric sparse planar array in the differential domain by Dong Lv, Guojin Feng, Fengshou Gu
- Scaled containment control for first/Second-order multi-agent systems in a noisy environment by Chongyang Wang, Shuzhi Sam Ge, Yingxue Du
- Successive ridge detection framework: A novel method for valve stiction detection by Xun Lang, Songhua Liu and Bingfei Dong
- Active disturbance rejection control with neural network-based ESO for gas turbine control system by fractional fuzzy-PSO optimization by Sara Majidi Shilsar, Alireza Khosravi and Hamed Mojallali