Aim and Scope
Neutrosophic and Information Fusion (NIF) is an international peer-reviewed journal devoted to theoretical, methodological, and applied research on neutrosophic systems, information fusion, and computational approaches for reasoning with uncertain, incomplete, inconsistent, and indeterminate information.
The journal provides a forum for advances in neutrosophic theory and their integration with information fusion, data analysis, intelligent systems, optimization, and decision-support methodologies. NIF particularly welcomes contributions that introduce new mathematical models, fusion operators, aggregation mechanisms, algorithms, decision frameworks, or computational methods for combining and interpreting information from multiple and potentially conflicting sources.
Topics of interest include, but are not limited to:
Neutrosophic sets, logic, probability, statistics, and algebraic structures
Single-valued, interval-valued, linguistic, refined, and generalized neutrosophic systems
Neutrosophic information fusion and multi-source data fusion
Evidence aggregation and uncertainty-aware information integration
Aggregation operators, similarity, distance, entropy, and divergence measures
Decision making and multi-criteria decision analysis under uncertainty
Evidence theory and belief-based reasoning
Fuzzy, neutrosophic, and hybrid uncertainty models
Knowledge representation and approximate reasoning
Data fusion, sensor fusion, and heterogeneous information integration
Optimization and computational intelligence
Machine learning and artificial intelligence under uncertainty
Pattern recognition, classification, and clustering with uncertain information
Explainable and trustworthy intelligent decision systems
Risk, reliability, and uncertainty assessment
Intelligent information processing and decision-support systems
Applications in engineering, healthcare, finance, supply chains, cybersecurity, IoT, sustainability, and other data-intensive domains
Applied studies are welcome when neutrosophic modeling or information fusion constitutes a substantive methodological contribution rather than being used only as a secondary analytical technique.
NIF aims to connect the mathematical foundations of neutrosophic systems with modern information-fusion methodologies, supporting rigorous research that improves the representation, integration, analysis, and decision-making of complex uncertain information.