International Journal of Intelligent Computing and Cybernetics

Aims & Scope

International Journal of Intelligent Computing and Cybernetics promotes intelligent computing and cybernetics methodologies in order to solve real life problems mainly from engineering and management systems domains.

The journal will mainly focus on the real life problems, which can suitably be handled through intelligent/soft computing and cybernetics paradigms.

International Journal of Intelligent Computing and Cybernetics will provide a unique platform for publishing the recent advances in applications, practices, and methodologies concerning with cybernetic systems.

International Journal of Intelligent Computing and Cybernetics focuses on studying and understanding the underlying principles of natural computation and control, and how these theories and technologies can be adopted or modified to extend and enrich computer science, and enrich the communication and control in society and in individual human beings.

Algorithms, techniques and theories in these fields have been successfully applied to a wide range of complex real-world problems.

International Journal of Intelligent Computing and Cybernetics is an international forum for publication of original papers in all disciplines of intelligent computing and cybernetics.

The following application areas will be promoted for possible publication: • agent based systems • autonomous reasoning • big data analytics • chaotic system modelling • data mining • decision support • distributed artificial intelligence • engineering design optimization • fault diagnosis • intelligent production systems (industry 4.0) • industrial engineering and operations research • man-machine interface • intelligent manufacturing systems • power and energy systems • process and system control/optimization • intelligent robotics • system identification • uncertainty handling in complex systems.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.6
2024	2.20

SJR (SCImago Journal Rank)

Year	Value
2024	0.382

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	27

Journal Rank

Year	Value
2024	14230

Journal Citation Indicator

Year	Value
2024	314

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning

  Citation: 511

  Authors: Haibin, Peixin

• Colonial competitive algorithm

  Citation: 180

  Authors: Esmaeil, Farzad, Ramin, Caro

• Design and implementation of construction cost prediction model based on SVM and LSSVM in industries 4.0

  Citation: 157

  Authors: Miao, Ashutosh

• Intelligent water drops algorithm

  Citation: 136

  Authors: Hamed

• Bibliometric analysis on Pythagorean fuzzy sets during 2013–2020

  Citation: 72

  Authors: Mingwei, Yanqiu, Riqing

• Solving two‐armed Bernoulli bandit problems using a Bayesian learning automaton

  Citation: 63

  Authors: Ole‐Christoffer

• A survey of inverse reinforcement learning techniques

  Citation: 59

  Authors: Shao, Er

• Concept of Yager operators with the picture fuzzy set environment and its application to emergency program selection

  Citation: 53

  Authors: Muhammad, Muhammad Ali, Saifullah, Saleem

• A systematic survey on deep learning and machine learning approaches of fake news detection in the pre- and post-COVID-19 pandemic

  Citation: 53

  Authors: Rajshree, Yugandhara, Priya, Prathamesh P.

• A novel approach to emergency risk assessment using FMEA with extended MULTIMOORA method under interval-valued Pythagorean fuzzy environment

  Citation: 53

  Authors: Huimin, Lelin, Feng, Lunyan, Qing

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