Aim and Scope
The Journal of Neutrosophic and Fuzzy Systems (JNFS) is an international peer-reviewed journal dedicated to theoretical, computational, and applied research on neutrosophic systems, fuzzy systems, and related approaches for modeling uncertainty, vagueness, indeterminacy, and incomplete information.
The journal publishes original research and review articles that advance the mathematical foundations, methodologies, algorithms, and applications of fuzzy and neutrosophic theories. Particular emphasis is placed on work that introduces new models, operators, mathematical structures, optimization methods, decision frameworks, or computational techniques with a clear contribution to uncertainty modeling.
Topics of interest include, but are not limited to:
Neutrosophic and fuzzy sets, systems, and logic
Generalized fuzzy and neutrosophic models
Plithogenic, intuitionistic, interval-valued, hesitant, type-2, Pythagorean, q-rung, spherical, and related uncertainty frameworks
Fuzzy and neutrosophic algebra, topology, graphs, geometry, probability, and statistics
Aggregation operators, similarity measures, entropy, and information fusion
Multi-criteria decision making and group decision models
Optimization and operations research under uncertainty
Computational intelligence, machine learning, and artificial intelligence
Classification, clustering, pattern recognition, and data analytics
Intelligent and explainable decision-support systems
Risk, reliability, control, and uncertainty-aware modeling
Applications in engineering, healthcare, finance, supply chains, agriculture, sustainability, energy, IoT, cybersecurity, education, and related fields
Applied studies are welcome when fuzzy, neutrosophic, or related uncertainty methodologies constitute a substantive part of the scientific contribution rather than a secondary analytical tool.
JNFS seeks to bridge mathematical theory and practical applications, supporting rigorous research that advances the understanding, computation, and use of uncertain and indeterminate information.