International Journal of Intelligent Computing and Cybernetics

Scope & Guideline

Elevating Academic Discourse in Intelligent Technologies

Introduction

Delve into the academic richness of International Journal of Intelligent Computing and Cybernetics with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN1756-378x
PublisherEMERALD GROUP PUBLISHING LTD
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 2008 to 2024
AbbreviationINT J INTELL COMPUT / Int. J. Intell. Comput. Cybern.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressFloor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE LS1 4DL, ENGLAND

Aims and Scopes

The International Journal of Intelligent Computing and Cybernetics primarily focuses on advanced computational techniques and their applications across various domains, emphasizing the intersection between intelligent systems and cybernetic processes. The journal aims to disseminate innovative research that contributes to the development of intelligent computing methodologies and their practical applications in real-world scenarios.
  1. Intelligent Systems Development:
    Research on the design, implementation, and evaluation of intelligent systems, including artificial intelligence, machine learning, and deep learning methodologies.
  2. Cybernetics and Control Systems:
    Exploration of control theory and cybernetic principles applied to intelligent systems, focusing on feedback mechanisms and adaptive control.
  3. Multi-Criteria Decision-Making:
    Methods and algorithms that facilitate decision-making processes in uncertain environments, emphasizing fuzzy logic, intuitionistic fuzzy sets, and linguistic variables.
  4. Data Analysis and Processing:
    Innovative techniques for data analysis, including machine learning, statistical methods, and optimization algorithms, aimed at extracting meaningful insights from complex datasets.
  5. Application of Intelligent Computing:
    Practical applications of intelligent computing methodologies across various fields such as healthcare, finance, agriculture, and environmental monitoring.
  6. Emerging Technologies and Trends:
    Focus on the integration of emerging technologies such as the Internet of Things (IoT), big data, and blockchain with intelligent computing approaches.
The International Journal of Intelligent Computing and Cybernetics is witnessing a surge in interest in several innovative themes that reflect current technological advancements and societal needs. These emerging scopes are indicative of the journal's responsiveness to the evolving landscape of intelligent computing and cybernetics.
  1. Deep Learning Innovations:
    A significant increase in research related to deep learning techniques, particularly in applications like image and speech recognition, indicating the growing importance and effectiveness of these methods.
  2. Integration of IoT and Intelligent Systems:
    Emerging themes focusing on the integration of IoT technologies with intelligent computing, addressing challenges in smart cities, healthcare, and industrial automation.
  3. Explainable AI (XAI):
    A rising focus on explainability in AI models, aiming to enhance transparency and trust in AI systems, especially in critical applications such as healthcare and finance.
  4. Hybrid Decision-Making Models:
    An upsurge in the development of hybrid models that combine multiple decision-making frameworks, particularly utilizing fuzzy logic and machine learning to tackle complex problems.
  5. Sustainable Computing Solutions:
    Growing interest in developing intelligent computing solutions that promote sustainability, including energy-efficient algorithms and eco-friendly applications.

Declining or Waning

While the journal continues to thrive in numerous areas, some themes have shown a decline in focus over recent years. This waning interest may result from the rapid evolution of research priorities and the emergence of new technologies that shift the attention of researchers.
  1. Traditional Statistical Methods:
    There has been a noticeable decrease in publications centered on traditional statistical analysis methods as researchers increasingly favor advanced machine learning and AI techniques.
  2. Basic Machine Learning Techniques:
    Basic machine learning approaches are becoming less prominent as the field evolves toward more complex architectures such as deep learning and ensemble methods that offer superior performance.
  3. Generic Cybersecurity Approaches:
    The journal has seen a decline in generic cybersecurity methodologies, as there is a growing emphasis on specialized techniques that leverage AI and machine learning for enhanced security.
  4. Single-Domain Applications:
    Research focusing exclusively on single-domain applications is waning, with a shift towards interdisciplinary approaches that integrate knowledge and methodologies from multiple domains.

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