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Modeling, Identification and Control - The Research Council of Norway | 2024 Cite Score:1.8 | Q3

Modeling, Identification and Control Journal With Cite Score

Cite Score and Journal Rank of Modeling, Identification and Control

  • About: The Modeling, Identification and Control journal publishes original research articles, technical papers, and reviews on various topics related to modeling, system identification, and control. This includes system dynamics modeling, parameter estimation, control system design, adaptive control, robust control, and applications in different engineering fields. The journal aims to advance the understanding and application of these methodologies to improve system performance and reliability.
  • Objective
    The primary objective of MIC is to provide a platform for high-quality research and scholarly discussion on modeling, identification, and control techniques. The journal seeks to promote the exchange of innovative ideas, support the development of new methodologies, and enhance the practical application of these techniques in solving complex engineering problems.
  • Interdisciplinary Approach
    Modeling, Identification and Control adopts an interdisciplinary approach, recognizing that research in these areas often intersects with fields such as artificial intelligence, signal processing, optimization, and computer science. The journal encourages contributions that integrate these diverse perspectives to address complex challenges and develop comprehensive solutions for system modeling, identification, and control.
  • Impact and Significance
    The journal has a significant impact on the engineering and applied sciences communities by providing valuable insights and practical recommendations for researchers, engineers, and practitioners. Its influence is reflected in its ability to shape research directions, drive advancements in modeling and control technologies, and contribute to the development of more efficient and effective systems. MIC plays a crucial role in advancing knowledge and practice in these critical areas.

  • Editor-in-Chief:  

  • Scope: The Modeling, Identification and Control (MIC) journal focuses on the theoretical and practical aspects of modeling, system identification, and control theory. It provides a platform for disseminating research that advances the understanding and application of these fundamental areas in systems and control engineering.
  • System Modeling:
    Research on techniques for developing accurate and efficient mathematical models of dynamic systems
    Innovations in modeling approaches for complex systems across various domains such as mechanical, electrical, chemical, and biological systems
    Case studies on the application of system modeling in real-world scenarios
    Trends in model-based design and simulation
    Future directions for improving system modeling methodologies
  • System Identification:
    Research on methods for identifying system parameters and structures from experimental data
    Innovations in identification techniques, including both classical and modern approaches
    Case studies on practical applications of system identification in different industries
    Trends in adaptive and real-time identification methods
    Future directions for enhancing system identification accuracy and efficiency
  • Control Theory and Applications:
    Research on control strategies and algorithms for managing dynamic systems
    Innovations in control theory, including feedback, feedforward, adaptive, and robust control
    Case studies on the implementation of control techniques in various applications such as robotics, automotive systems, and industrial processes
    Trends in the integration of control theory with emerging technologies such as machine learning and artificial intelligence
    Future directions for advancing control theory and its applications
  • System Integration and Optimization:
    Research on integrating modeling, identification, and control techniques to create effective system solutions
    Innovations in optimization methods for improving system performance and efficiency
    Case studies on the integration of modeling, identification, and control in complex systems
    Trends in the development of holistic approaches to system design and optimization
    Future directions for enhancing system integration and optimization methodologies
  • Data-Driven Approaches:
    Research on the use of data-driven methods in system modeling, identification, and control
    Innovations in leveraging data analytics, machine learning, and big data for system analysis and design
    Case studies on the application of data-driven approaches in various fields
    Trends in the integration of data-driven techniques with traditional modeling and control methods
    Future directions for expanding the role of data-driven approaches in system engineering
  • Educational and Professional Development:
    Research on educational strategies and training programs related to modeling, identification, and control
    Innovations in curriculum development, pedagogical approaches, and professional development
    Case studies on effective knowledge transfer and skill development in these areas
    Trends in the evolution of education and training for modeling, identification, and control
    Future directions for enhancing educational and professional opportunities in this field
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  0332-7353

    Electronic ISSN:  1890-1328

  • Abstracting and Indexing:  Scopus

  • Imapct Factor :  

  • Subject Area and Category:   Computer Science, Computer Science Applications, Software, Engineering, Control and Systems Engineering, Mathematics, Modeling and Simulation

  • Publication Frequency:  Quarterly

  • H Index:  31

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  Control and Systems Engineering

    Q4:  

  • Cite Score:  1.8

  • SNIP:  0.508

  • Journal Rank(SJR):  0.259