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Journal of Uncertain Systems - World Academic | 2024 Cite Score:2.4 | Q2

Journal of Uncertain Systems With Cite Score

Cite Score and Journal Rank of Journal of Uncertain Systems

  • About: Journal of Uncertain Systems is a peer-reviewed journal dedicated to the study of systems characterized by uncertainty. The journal addresses both theoretical and practical aspects of uncertainty in various types of systems, including engineering, economics, and decision-making processes.
  • Objective: The primary objective of the Journal of Uncertain Systems is to advance the understanding of systems where uncertainty plays a significant role. This includes the development of new theories, methodologies, and applications that address the challenges posed by uncertainty in system modeling, analysis, and design.
  • Impact and Audience: The Journal of Uncertain Systems has a significant impact on the field of systems science by providing a platform for the dissemination of research that addresses the complexities and challenges associated with uncertainty. The journals focus on both theoretical and applied research makes it a valuable resource for academics, researchers, and practitioners working in areas where uncertainty is a critical factor.

  • Editor-in-Chief:  Jinwu Gao

  • Scope: Journal of Uncertain Systems is a scholarly publication focused on advancing research in the field of uncertainty modeling and systems analysis. It provides a platform for presenting innovative methods, theoretical advancements, and practical applications related to uncertainty in various systems.
  • Key Areas Covered:
    1. Uncertainty Modeling: Research on techniques and methodologies for modeling uncertainty in systems. This includes fuzzy logic, probabilistic models, and evidence theory.
  • 2. Decision Making Under Uncertainty: Studies on decision-making processes and strategies in the presence of uncertainty. Topics include risk assessment, decision theory, and multi-criteria decision analysis.
  • 3. Stochastic Processes: Papers on stochastic modeling and analysis, including Markov processes, queuing theory, and simulation of stochastic systems.
  • 4. Robust Optimization: Research on optimization techniques that account for uncertainty. This includes robust optimization, interval optimization, and scenario-based methods.
  • 5. Uncertain Data Analysis: Articles focusing on the analysis and interpretation of uncertain or imprecise data. Topics include data fusion, uncertainty quantification, and handling incomplete data.
  • 6. Systems Engineering: Studies on the application of uncertainty modeling in systems engineering. This includes reliability analysis, fault tolerance, and system design under uncertainty.
  • 7. Applications in Engineering and Science: Research on the application of uncertainty methods in various engineering and scientific domains, such as control systems, environmental modeling, and biomedical engineering.
  • 8. Computational Techniques: Papers on computational methods and algorithms for managing and analyzing uncertainty. This includes numerical methods, simulation techniques, and software tools.
  • 9. Uncertainty in Artificial Intelligence: Research on the integration of uncertainty modeling with artificial intelligence techniques. Topics include uncertain reasoning, probabilistic reasoning, and machine learning with uncertain data.
  • 10. Theoretical Foundations: Articles exploring the theoretical underpinnings of uncertainty modeling. This includes mathematical foundations, theoretical frameworks, and new theoretical developments.
  • 11. Uncertainty in Risk Management: Studies on managing and mitigating risks in the presence of uncertainty. Topics include risk assessment frameworks, risk modeling, and uncertainty-based decision support systems.
  • 12. Uncertainty and Reliability Engineering: Research on reliability analysis and engineering methods considering uncertainty. This includes reliability prediction, failure analysis, and uncertainty in reliability assessment.
  • 13. Policy and Strategic Decision Making: Papers on the role of uncertainty in policy and strategic decision-making. This includes analysis of uncertainty impacts on policy development and strategic planning.
  • 14. Uncertainty in Financial Systems: Research on uncertainty modeling in financial systems, including risk management, portfolio optimization, and financial forecasting.
  • 15. Case Studies and Applications: Practical case studies demonstrating the application of uncertainty modeling techniques in real-world scenarios. This includes industry applications and interdisciplinary studies.
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  • Print ISSN:  17528909

    Electronic ISSN:  17528917

  • Abstracting and Indexing:  Scopus

  • Imapct Factor :  

  • Subject Area and Category:   Computer Science, Artificial Intelligence, Computer Vision and Pattern Recognition, Mathematics, Control and Optimization

  • Publication Frequency:  

  • H Index:  22

  • Best Quartile:

    Q1:  

    Q2:  Artificial Intelligence

    Q3:  

    Q4:  

  • Cite Score:  2.4

  • SNIP:  0.691

  • Journal Rank(SJR):  0.422