IEEE-CAA Journal of Automatica Sinica - Impact Factor

IEEE-CAA Journal of Automatica Sinica | 2024 Impact Factor:19.2 | Cite Score:28.2 | Q1

Impact Factor and Journal Rank of IEEE-CAA Journal of Automatica Sinica

About: The IEEE/CAA Journal of Automatica Sinica (JAS) is a highly regarded, peer-reviewed academic journal co-sponsored by the Institute of Electrical and Electronics Engineers (IEEE) and the Chinese Association of Automation (CAA). It serves as a premier platform for disseminating significant research contributions in the field of automation science and engineering. The journal aims to promote advancements in automation theory and practice, spanning a wide range of topics from control systems and intelligent automation to robotics and artificial intelligence.
Content Types: Research Articles: In-depth original research papers presenting new theoretical developments, methodologies, and applications in automation and control. Review Articles: Comprehensive reviews of current trends, challenges, and future directions in specific areas of automation science and engineering. Technical Notes: Brief reports on innovative techniques, preliminary research findings, and emerging technologies in the field.
High Standards and Impact: Peer-Reviewed: The journal employs a rigorous peer-review process to ensure the quality, accuracy, and relevance of published research. Citation Impact: Articles published in JAS are widely cited, reflecting the journal significant influence and impact on the field of automation. Reputation: Recognized as a leading publication in automation and control, the journal is known for publishing high-quality, impactful research.
Global Reach: International Contributions: The journal attracts contributions from researchers and practitioners worldwide, offering diverse and global perspectives on automation science and engineering. Broad Accessibility: Research articles are accessible through academic libraries, online databases, and digital platforms, ensuring wide dissemination and impact.
Significance: IEEE/CAA Journal of Automatica Sinica is a prestigious and influential publication that significantly contributes to the advancement of knowledge, innovation, and practice in the field of automation science and engineering. Its broad scope, high standards, and global reach make it an essential resource for researchers, practitioners, and policymakers dedicated to advancing automation technology and its applications.

Journal Home: Journal Homepage

Editor-in-Chief: Qing-Long Han

Scope: It aims to advance the theory, design, and application of control, automation, and systems engineering. The journal is co-sponsored by the IEEE and the Chinese Association of Automation (CAA).
The scope of the journal encompasses a wide range of topics in automation and control engineering, including but not limited to:
Control Systems: Research on the theory, design, and application of control systems, including linear and nonlinear control, adaptive control, and robust control.
Intelligent Automation: Studies on the integration of artificial intelligence with automation systems to enhance decision-making, autonomy, and efficiency.
Robotics: Contributions to the field of robotics, covering areas such as robot design, motion planning, navigation, and human-robot interaction.
Optimization: Research on optimization techniques and their applications in automation, including algorithm development and implementation for various industrial processes.
Networked and Distributed Systems: Exploration of the control and optimization of networked systems, including multi-agent systems, cyber-physical systems, and Internet of Things (IoT).
Manufacturing and Industrial Automation: Studies focusing on automation in manufacturing processes, smart factories, and Industry 4.0 technologies.
Biomedical Engineering: Application of automation and control theory in biomedical systems, such as medical devices, healthcare automation, and biological systems modeling.
System Identification and Modeling: Research on methods for identifying, modeling, and simulating dynamic systems to improve control and automation.
Sensor Networks and Data Fusion: Investigation of sensor technologies, data fusion techniques, and their applications in automated systems and environments.
Autonomous Vehicles and Systems: Studies on the design, control, and operation of autonomous vehicles, including ground, aerial, and underwater vehicles.