International Journal of Hybrid Intelligent Systems

Aims & Scope

Hybridization of intelligent systems is a promising research field of modern Artificial Intelligence concerned with the development of the next generation of intelligent systems.

A fundamental stimulus to the investigations of Hybrid Intelligent Systems (HIS) is the awareness in the academic communities that combined and integrated approaches will be necessary if the remaining tough problems in artificial intelligence are to be solved.

Recently, hybrid intelligent systems are becoming popular due to their capabilities in handling many real world complex problems, involving imprecision, uncertainty and vagueness, high-dimensionality.

The International Journal of Hybrid Intelligent Systems (IJHIS) is a peer refereed journal on the theory and applications of hybrid and integrated intelligent systems.

The key objective of IJHIS is to provide the academic community with a medium for presenting original research and applications related to the simultaneous use of two or more intelligent techniques.

Rather than publishing papers in one particular area of expertise, the journal aims to be the main forum for publishing papers that involve the use of two or more intelligent techniques and approaches, such as neural networks, traditional knowledge-based methods, fuzzy techniques, genetic algorithms, agent-based techniques, case based reasoning, etc.

The combination or integration of more distinct methodologies can be done in any form, either by a modular integration of two or more intelligent methodologies, which maintains the identity of each methodology, or by fusing one methodology into another, or by transforming the knowledge representation in one methodology into another form of representation, characteristic to another methodology.

View Aims & Scope

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Metrics & Ranking

Journal Rank

Year	Value
2024	15181

Journal Citation Indicator

Year	Value
2024	76

SJR (SCImago Journal Rank)

Year	Value
2024	0.349

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	10

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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

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, 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.

• Impact of static and adaptive mutation techniques on the performance of Genetic Algorithm

  Citation: 120

  Authors: B.R.

• Multi-Classifier Systems: Review and a roadmap for developers

  Citation: 97

  Authors: Romesh, Vasile

• Hybrid Intelligence in Software Release Planning

  Citation: 66

  Authors: Günther, An

• Federated learning: Applications, challenges and future directions

  Citation: 55

  Authors: Subrato, M. Rubaiyat Hossain, Prajoy, V.B. Surya

• CO-ResNet: Optimized ResNet model for COVID-19 diagnosis from X-ray images

  Citation: 42

  Authors: Subrato, Prajoy, M. Rubaiyat Hossain, V.B. Surya

• A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees

  Citation: 40

  Authors: Doina, Adrian, Vasant

• On diversity and accuracy of homogeneous and heterogeneous ensembles

  Citation: 37

  Authors: Shun, Wenjia

• Time series prediction using ensembles of ANFIS models with genetic optimization of interval type-2 and type-1 fuzzy integrators

  Citation: 36

  Authors: Jesus, Patricia, Oscar

• Investigation of evolutionary optimization methods of TSK fuzzy model for real estate appraisal

  Citation: 35

  Authors: Dariusz, Tadeusz, Bogdan, Krzysztof

• Evolutionary reinforcement learning of artificial neural networks

  Citation: 34

  Authors: Nils T., Gerald

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