International Journal of System Dynamics Applications
Scope & Guideline
Unraveling Complexity through Rigorous Research.
Introduction
Aims and Scopes
- System Dynamics Modeling:
The journal emphasizes the development and application of system dynamics models to understand complex systems and their behaviors, allowing for simulation and analysis of dynamic interactions. - Computational Intelligence Techniques:
It showcases research on the integration of computational intelligence, including fuzzy logic, genetic algorithms, and machine learning, to enhance decision-making processes and system performance. - Application in Emerging Technologies:
The journal covers the application of system dynamics in emerging technologies, such as IoT, cloud computing, and smart systems, emphasizing their role in modern computing and industrial applications. - Sustainability and Resource Management:
A core focus is on sustainability, particularly in resource management and operational efficiency, with studies addressing environmental impacts and sustainable practices. - Healthcare and Epidemiology:
Research related to healthcare systems, including modeling for disease spread, healthcare resource allocation, and clinical decision-making, is a significant area of interest.
Trending and Emerging
- Healthcare Analytics and COVID-19 Research:
There is a significant increase in research focused on healthcare analytics, particularly in the context of COVID-19, illustrating the importance of system dynamics in managing health crises. - IoT and Smart Systems Integration:
Emerging studies on the integration of IoT technologies with system dynamics modeling signify a trend towards understanding complex interactions in smart environments. - Sustainability and Environmental Impact Studies:
Research addressing sustainability issues, particularly in resource management and environmental impact assessments, has gained traction, aligning with global sustainability goals. - Artificial Intelligence and Machine Learning Applications:
The incorporation of AI and machine learning techniques in system dynamics is a growing trend, showcasing innovative approaches to problem-solving in various domains. - Decision-Making Frameworks in Uncertain Environments:
Papers focusing on decision-making frameworks that account for uncertainty and risk management are increasingly prominent, reflecting the need for adaptive strategies in volatile conditions.
Declining or Waning
- Traditional Manufacturing Techniques:
Research related to conventional manufacturing processes has seen a decline, as the focus shifts towards smart manufacturing and automation technologies. - Basic Statistical Methods in Analysis:
Papers solely relying on basic statistical methods without advanced modeling or computational techniques have become less frequent, as the journal embraces more sophisticated analytical approaches. - Non-Dynamic Systems Research:
There is a waning interest in studies that do not incorporate dynamic modeling or system dynamics principles, as the journal aims to maintain a clear focus on dynamic systems.
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