Journal of Advanced Computational Intelligence and Intelligent Informatics

Scope & Guideline

Fostering Collaboration in Advanced Computational Intelligence

Introduction

Delve into the academic richness of Journal of Advanced Computational Intelligence and Intelligent Informatics 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
ISSN1343-0130
PublisherFUJI TECHNOLOGY PRESS LTD
Support Open AccessYes
CountryJapan
TypeJournal
Convergefrom 1997 to 2024
AbbreviationJ ADV COMPUT INTELL / J. Adv. Comput. Intell. Inform.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address1-15-7, UCHIKANDA, CHIYODA-KU, UNIZO UCHIKANDA 1-CHOME BLDG 2F, TOKYO 101-0047, JAPAN

Aims and Scopes

The Journal of Advanced Computational Intelligence and Intelligent Informatics focuses on the intersection of computational intelligence and various application areas, emphasizing innovative methodologies and intelligent systems.
  1. Computational Intelligence Techniques:
    The journal covers a wide range of computational intelligence methods, including neural networks, fuzzy logic, and evolutionary algorithms, applied to solve complex real-world problems.
  2. Intelligent Systems and Applications:
    Research published in the journal often involves the development and application of intelligent systems in diverse fields such as healthcare, robotics, and education.
  3. Data Analysis and Machine Learning:
    The journal emphasizes methodologies for data analysis, including machine learning and deep learning techniques, aimed at extracting insights from large datasets.
  4. Human-Machine Interaction:
    There is a significant focus on improving human-machine interaction through intelligent systems, including robotics and assistive technologies.
  5. Decision-Making Models:
    Research often involves sophisticated decision-making models such as multi-criteria decision-making and reinforcement learning, aimed at optimizing various processes.
The journal has witnessed the emergence of new themes and an increased focus on specific areas of research that reflect current technological trends and societal needs.
  1. Artificial Intelligence in Healthcare:
    There is a growing trend in applying AI techniques to healthcare, particularly in areas like disease diagnosis, patient monitoring, and treatment optimization.
  2. Robotics and Automation:
    Research related to robotics, especially in automation and intelligent control systems, has gained momentum, reflecting the increasing interest in autonomous systems.
  3. Emotion Recognition and Affective Computing:
    The journal has seen a rise in studies focused on emotion recognition technologies, especially using facial expressions and physiological signals, which are essential for human-computer interaction.
  4. Sustainable and Smart Technologies:
    Emerging themes include the application of computational intelligence in sustainable practices and smart technologies, addressing environmental challenges and enhancing efficiency.
  5. Multimodal Data Fusion:
    The integration of multiple data sources (e.g., audio, visual) for enhanced analysis and decision-making is increasingly prevalent, indicating a trend towards more complex data environments.

Declining or Waning

While the journal has consistently explored a variety of themes, certain areas have seen a noticeable decline in emphasis over recent years.
  1. Traditional Statistical Methods:
    There has been a reduction in the publication of papers focused solely on traditional statistical methods without the integration of computational intelligence, indicating a shift towards more advanced techniques.
  2. Basic Algorithmic Approaches:
    Papers detailing basic algorithmic approaches without innovative enhancements or applications are becoming less frequent, as the focus shifts towards novel methodologies and applications.
  3. Generalized Applications in Non-Specific Domains:
    Research that applies computational intelligence in overly broad or non-specific domains is declining, with a trend towards more targeted and application-driven studies.

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