International Journal of Knowledge-Based and Intelligent Engineering Systems

Scope & Guideline

Empowering Innovations in Knowledge-Based Technologies

Introduction

Immerse yourself in the scholarly insights of International Journal of Knowledge-Based and Intelligent Engineering Systems with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN1327-2314
PublisherIOS PRESS
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 2004 to 2024
AbbreviationINT J KNOWL-BASED IN / Int. J. Knowl.-Based Intell. Eng. Syst.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressNIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS

Aims and Scopes

The International Journal of Knowledge-Based and Intelligent Engineering Systems focuses on the intersection of knowledge-based systems and intelligent engineering. The journal aims to advance the methodologies and applications of decision-making frameworks, particularly those that utilize fuzzy logic, neutrosophic sets, and multi-attribute decision-making (MADM) techniques.
  1. Multi-Attribute Decision-Making (MADM):
    The journal emphasizes methodologies for multi-attribute decision-making, employing various fuzzy and neutrosophic approaches to address complex decision scenarios across different domains.
  2. Intelligent Systems and Algorithms:
    Research related to the development and application of intelligent algorithms, including machine learning, artificial intelligence, and optimization techniques, is a core focus, particularly in enhancing decision-making processes.
  3. Applications in Diverse Fields:
    The journal showcases applications of knowledge-based systems in various fields such as education, healthcare, environmental management, and engineering, demonstrating the practical impact of research findings.
  4. Fuzzy Logic and Neutrosophic Theory:
    A significant portion of the journal's articles explores fuzzy logic and neutrosophic theories, providing innovative frameworks for handling uncertainty and imprecision in decision-making.
  5. Data Analytics and Decision Support:
    The integration of big data analytics with decision-support systems is highlighted, showcasing how advanced data processing techniques can enhance the effectiveness of decision-making frameworks.
Recent publications in the journal reveal several emerging themes that reflect current trends in knowledge-based systems and intelligent engineering. These topics are gaining traction and are likely to shape future research directions.
  1. Advanced Fuzzy and Neutrosophic Decision-Making Techniques:
    There is an increasing trend in the development and application of advanced fuzzy and neutrosophic decision-making techniques, which are being applied to complex evaluation problems across various domains.
  2. Integration of Big Data and AI:
    The integration of big data analytics with artificial intelligence techniques is becoming a prominent theme, as researchers explore how these technologies can enhance decision-making processes and outcomes.
  3. Real-Time and Intelligent Systems:
    Emerging research focuses on real-time applications of intelligent systems, particularly in areas like autonomous vehicles and dynamic data processing, highlighting the growing importance of real-time decision-making capabilities.
  4. Sustainability and Energy Efficiency:
    Sustainability-related themes, particularly energy efficiency and environmental impact assessments, are increasingly prevalent, reflecting a broader societal focus on sustainable development and resource management.
  5. Educational Technology and Evaluation:
    The application of intelligent decision-making frameworks in educational settings, particularly regarding teaching quality and learning evaluations, is gaining attention, indicating a trend towards improving educational outcomes through technology.

Declining or Waning

While the journal has seen growth in several areas, some themes appear to be declining in prominence in recent publications. This reflects a shifting focus towards more contemporary methodologies and applications.
  1. Traditional Decision-Making Frameworks:
    There is a noticeable decline in the publication of articles utilizing traditional decision-making frameworks that do not incorporate advanced fuzzy or neutrosophic approaches, as the journal increasingly favors innovative methodologies.
  2. Basic Machine Learning Techniques:
    Basic or introductory machine learning techniques are appearing less frequently, as more complex and hybrid methodologies take precedence, indicating a shift toward advanced applications and integrations.
  3. General Optimization Techniques:
    Research centered on general optimization techniques without the integration of intelligent systems or advanced algorithms is becoming less common, suggesting a preference for more sophisticated approaches.
  4. Non-application-focused Research:
    The journal is moving away from purely theoretical discussions that lack practical applications, favoring studies that demonstrate clear applications of knowledge-based systems in real-world scenarios.

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