International Journal of Intelligent Engineering Informatics

Scope & Guideline

Navigating the Frontiers of Computer Science and AI.

Introduction

Delve into the academic richness of International Journal of Intelligent Engineering 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
ISSN1758-8715
PublisherINDERSCIENCE ENTERPRISES LTD
Support Open AccessNo
Country-
TypeJournal
Convergefrom 2022 to 2024
AbbreviationINT J INTELL ENG INF / Int. J. Intell. Eng. Inform.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressWORLD TRADE CENTER BLDG, 29 ROUTE DE PRE-BOIS, CASE POSTALE 856, CH-1215 GENEVA, SWITZERLAND

Aims and Scopes

The International Journal of Intelligent Engineering Informatics focuses on advancing the field of intelligent engineering through innovative methodologies and interdisciplinary approaches. It encompasses a broad range of topics that intersect artificial intelligence, machine learning, data analytics, and engineering applications.
  1. Artificial Intelligence and Machine Learning:
    The journal publishes research on various AI and machine learning techniques, including deep learning, reinforcement learning, and hybrid models, aimed at solving complex engineering problems.
  2. Data Analytics and Processing:
    Research on data analysis methodologies, including big data processing, data mining, and statistical analysis, is a core focus, particularly as it relates to engineering and informatics.
  3. Image and Signal Processing:
    The journal emphasizes methods for image and signal processing, including computer vision applications, medical imaging, and noise reduction techniques.
  4. Optimization Techniques:
    A significant portion of research is dedicated to optimization algorithms and their applications in various engineering fields, including resource allocation, routing, and scheduling problems.
  5. Interdisciplinary Applications:
    The journal promotes interdisciplinary studies that apply intelligent engineering principles to diverse fields such as healthcare, environmental monitoring, and smart systems.
  6. Cybersecurity and Data Privacy:
    Research addressing cybersecurity challenges, including anomaly detection and secure data management within intelligent systems, is increasingly featured.
The journal has been actively embracing new themes and methodologies that reflect the evolving landscape of intelligent engineering and informatics. Recent trends indicate a strong focus on cutting-edge technologies and applications.
  1. Deep Learning and Neural Networks:
    There is an increasing emphasis on deep learning architectures and their applications in various domains, such as healthcare imaging, natural language processing, and predictive analytics.
  2. Explainable AI and Ethical Considerations:
    Research focusing on explainable AI is gaining traction, addressing the need for transparency and accountability in AI-driven systems, particularly in sensitive areas like healthcare.
  3. Hybrid and Multi-Modal Approaches:
    Emerging studies are exploring hybrid models that combine different machine learning techniques or integrate multiple data sources to enhance predictive performance and robustness.
  4. IoT and Smart Systems:
    The intersection of intelligent engineering with IoT technologies is increasingly prominent, showcasing applications in smart cities, healthcare monitoring, and environmental sensing.
  5. Sustainability and Environmental Applications:
    Research addressing environmental challenges through intelligent engineering solutions is on the rise, reflecting a growing awareness of sustainability in engineering practices.

Declining or Waning

While the journal has a wide-ranging focus, certain themes have seen a decrease in publication frequency, indicating a potential waning interest or saturation in those areas.
  1. Traditional Control Systems:
    There has been a noticeable decline in research focused solely on traditional control systems, as the field shifts towards more intelligent and adaptive control strategies that leverage AI.
  2. Basic Statistical Techniques:
    Research that primarily employs basic statistical methods without the integration of advanced machine learning or AI techniques is becoming less common, as the journal’s emphasis moves towards more sophisticated analytical approaches.
  3. Non-AI-Based Engineering Solutions:
    Papers presenting engineering solutions that do not incorporate AI or intelligent methodologies are appearing less frequently, reflecting a broader trend towards intelligent systems.

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