INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE

Scope & Guideline

Advancing Knowledge in Systems Science

Introduction

Welcome to the INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN0020-7721
PublisherTAYLOR & FRANCIS LTD
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1970 to 2024
AbbreviationINT J SYST SCI / Int. J. Syst. Sci.
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND

Aims and Scopes

The INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE focuses on the advancement of theoretical and practical aspects of systems science and engineering. It serves as a platform for researchers and practitioners to disseminate their findings on various topics related to systems theory, control systems, and networked systems.
  1. Systems Theory and Control:
    The journal emphasizes the development and application of systems theory, particularly in the context of control systems. This includes robust control, adaptive control, and model predictive control strategies.
  2. Multi-Agent Systems:
    Research on consensus and coordination among multiple agents is a core focus. This encompasses decentralized control strategies and event-triggered mechanisms for multi-agent systems.
  3. Cyber-Physical Systems:
    The journal explores the intersection of control systems and cyber-physical systems, addressing challenges such as security, resilience, and performance optimization in the presence of cyber threats.
  4. Event-Triggered Control:
    A significant portion of the published work revolves around event-triggered control strategies, which aim to reduce communication and computational load in control systems.
  5. Nonlinear Systems:
    There is a strong emphasis on the control and analysis of nonlinear systems, including the development of novel techniques for handling uncertainties and disturbances.
  6. Adaptive and Learning Systems:
    The journal features research on adaptive control systems that can learn from their environment and improve performance over time, utilizing techniques such as reinforcement learning.
The journal has witnessed an evolution in research trends, with several emerging themes gaining traction. These trends reflect the current challenges and innovations within systems science and engineering.
  1. Resilient Control Systems:
    There is an increasing focus on developing resilient control systems that can withstand cyber-attacks and other disruptions, highlighting the importance of security in modern control applications.
  2. Data-Driven Control:
    Research on data-driven control methodologies is on the rise, emphasizing the utilization of machine learning and statistical techniques to enhance control strategies based on real-time data.
  3. Adaptive and Learning Control:
    The trend toward adaptive control and learning systems, particularly in uncertain environments, is gaining momentum, as researchers explore ways to improve system performance through learning.
  4. Hybrid Systems and Multi-Modal Control:
    Emerging studies are focusing on hybrid systems that combine various control methods to achieve better performance, particularly in complex and uncertain environments.
  5. Event-Triggered and Networked Control:
    There is a growing emphasis on event-triggered control strategies in networked systems, aimed at optimizing communication and resource utilization in distributed environments.
  6. Fuzzy and Intelligent Control Systems:
    Research on fuzzy logic and intelligent control systems is trending, reflecting the need for more sophisticated approaches to handle uncertainties and nonlinearities in control applications.

Declining or Waning

While the journal continues to cover a broad array of topics within systems science, some areas have seen a decline in publication frequency. These waning themes may reflect a shift in research focus or emerging priorities in the field.
  1. Classical Control Techniques:
    There has been a noticeable decrease in the publication of papers focused on traditional control methods, such as PID control, as newer adaptive and intelligent control techniques gain prominence.
  2. Deterministic Modeling:
    Research centered around deterministic models has diminished, possibly due to a growing interest in stochastic and probabilistic approaches that better capture the complexities of real-world systems.
  3. Static Systems Analysis:
    Static analysis methods are becoming less prevalent as dynamic and time-varying system analyses gain traction, reflecting the need for more comprehensive modeling approaches.
  4. Basic Linear Systems:
    The focus on basic linear systems is waning, as the field moves towards more complex and nonlinear systems that require advanced control strategies.

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