Journal of Intelligent & Fuzzy Systems - Impact Factor

Journal of Intelligent & Fuzzy Systems - IOS Press | 2024 Impact Factor:1.0 | Cite Score:4.2 | Q2

Impact Factor and Journal Rank of Journal of Intelligent & Fuzzy Systems

About: The Journal of Intelligent & Fuzzy Systems publishes high-quality, peer-reviewed articles on the theory and application of intelligent and fuzzy systems. The journal aims to provide a platform for the dissemination of significant research findings and innovative methodologies in the field.
Objectives
The primary objectives of the journal are:
Advancing Intelligent Systems: To promote the development and application of intelligent systems and fuzzy logic.
Enhancing Decision-Making: To explore how intelligent and fuzzy systems can improve decision-making processes.
Encouraging Interdisciplinary Research: To foster interdisciplinary research that integrates artificial intelligence, fuzzy logic, and other scientific and engineering disciplines.
Disseminating Knowledge: To disseminate significant research findings and practical applications in intelligent and fuzzy systems.
Key Topics Covered
Fuzzy Logic: Theoretical advancements and practical applications of fuzzy logic.
Intelligent Systems: Development and application of intelligent systems in various domains.
Expert Systems: Design and implementation of expert systems using fuzzy logic and artificial intelligence.
Decision Support Systems: Use of intelligent and fuzzy systems in decision support.
Robotics and Automation: Applications of fuzzy logic in robotics and automation.
Machine Learning: Integration of fuzzy logic with machine learning techniques.
Pattern Recognition: Fuzzy and intelligent approaches to pattern recognition.
Control Systems: Design of control systems using fuzzy logic and intelligent methodologies.
Optimization: Fuzzy logic and intelligent methods for optimization problems.
Data Analysis: Application of fuzzy logic and intelligent systems in data analysis and interpretation.
Impact and Significance
The Journal of Intelligent & Fuzzy Systems contributes significantly to:
Scientific Advancement: By publishing cutting-edge research that advances the field of intelligent and fuzzy systems.
Industry Applications: By showcasing practical applications of intelligent and fuzzy systems in various industries.
Interdisciplinary Collaboration: By fostering collaboration between researchers and practitioners from different scientific and engineering disciplines.
Educational Resources: By providing valuable insights and resources for educators and students in the fields of artificial intelligence, fuzzy logic, and intelligent systems.

Journal Home: Journal Homepage

Editor-in-Chief: Mo M. Jamshidi

Scope: Journal of Intelligent & Fuzzy Systems is a prominent publication dedicated to the advancement of intelligent systems and fuzzy logic research. It serves as a critical platform for disseminating high-quality research that contributes to the development and application of intelligent and fuzzy systems across various domains.
Journal of Intelligent & Fuzzy Systems publishes innovative research contributions in the following areas:
Fuzzy Logic: Theoretical developments and practical applications of fuzzy logic, including fuzzy set theory, fuzzy inference systems, and fuzzy decision-making.
Intelligent Systems: Research on the design, implementation, and application of intelligent systems, including expert systems, neural networks, genetic algorithms, and hybrid systems.
Knowledge-Based Systems: Development and utilization of systems that leverage artificial intelligence and knowledge engineering for problem-solving and decision support.
Machine Learning and Data Mining: Techniques and applications of machine learning and data mining in intelligent and fuzzy systems, including pattern recognition, clustering, and classification.
Control Systems: Innovations in intelligent control systems and applications of fuzzy logic in control theory, including adaptive and robust control methodologies.
Optimization: Application of fuzzy logic and intelligent techniques to optimization problems in engineering, economics, management, and other fields.
Interdisciplinary Research: Contributions that integrate fuzzy logic and intelligent systems with other disciplines such as computer science, engineering, bioinformatics, and social sciences.