International Journal of Approximate Reasoning

Aims & Scope

The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications.

It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest.

Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning.

Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3
2024	3.20

Journal Rank

Year	Value
2024	7672

Journal Citation Indicator

Year	Value
2024	1543

SJR (SCImago Journal Rank)

Year	Value
2024	0.731

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	116

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Hesitant fuzzy information aggregation in decision making

  Citation: 1299

  Authors: Meimei, Zeshui

• Semantic hashing

  Citation: 837

  Authors: Ruslan, Geoffrey

• Multicriteria analysis with fuzzy pairwise comparison

  Citation: 548

  Authors: Hepu

• Three-way decision and granular computing

  Citation: 524

  Authors: Yiyu

• Probabilistic rough set approximations

  Citation: 505

  Authors: Yiyu

• Decision making in the TBM: the necessity of the pignistic transformation

  Citation: 500

  Authors: Philippe

• Dynamic intuitionistic fuzzy multi-attribute decision making

  Citation: 498

  Authors: Zeshui, Ronald R.

• Two views of the theory of rough sets in finite universes

  Citation: 474

  Authors: Y.Y.

• Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem

  Citation: 470

  Authors: Philippe

• NN-driven fuzzy reasoning

  Citation: 455

  Authors: Hideyuki, Isao

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