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Information Processing and Management of Uncertainty in Knowledge-Based Systems

21st International Conference, IPMU 2026, Rome, Italy, June 15–19, 2026, Proceedings, Part II

Medium: Buch
ISBN: 978-3-032-28996-4
Verlag: Springer
Erscheinungstermin: 12.06.2026
Lieferfrist: bis zu 10 Tage

This three-volume set CCIS 3019-3021 constitutes the proceedings of the 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026, held in Rome, Italy, during June 15-19, 2026.

The 111 full papers included in these volumes were carefully reviewed and selected from 254 submissions. They are organized into topical sections as follows:

Part I: Aggregation theory; Imprecise probabilities; Knowledge representation and modelling; Statistical inference and data analysis.

Part II: Robustness in economics and finance, Foundations of fuzzy sets;  Fuzzy and multivalued logic; Explainable AI and decision making.

Part III: Preference modelling; Cooperative automated systems; Fuzzy control: methods and applications; Fuzzy implication functions; Data mining.


Produkteigenschaften


  • Artikelnummer: 9783032289964
  • Medium: Buch
  • ISBN: 978-3-032-28996-4
  • Verlag: Springer
  • Erscheinungstermin: 12.06.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Communications in Computer and Information Science
  • Produktform: Kartoniert
  • Seiten: 514
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

.- Robustness in economics and finance.

.- Fuzzy Extensions of SDEs and the Non-Overlap of Crisp and Fuzzy
Solution Trajectories.

.- A fuzzy variational model for spatial innovation diffusion with uncertain
inter-regional influence.

.- A Risk Management Agent with Uncertainty Quantification for
Financial Trading.

.- Credal Ensemble Classification with Structural Discriminative
Gaussian-Bernoulli RBMs.

.- Enforcing Sparsity of Imprecise Transport Plans in Dempster-Shafer
Optimal Transport.

.- On the Calculation and Risk Analysis of Finite Interval Predictors.

.- Foundations of fuzzy sets.

.- New negations for notable restrictions on the membership degrees of
type-2 fuzzy sets.

.-  On type reductions with quantale based fuzzy sets .

.- A preliminary study on the use of dCF-integrals in Fuzzy Rule-Based
Classification Systems for Class Imbalance.

.- A duality relationship between similarity metrics and Mathew’s partial
metrics based on boundedness.

.- Representation of quasi-(pesudo-)metrics by means of fuzzy sets.

.- Behaviour of Morphological Operators in L-powersets of Additive
Groups Under Powerset Operators.

.- Penrose-Banzhaf Weighted Aggregation Operator with Sugeno-Weber
t-norms for Intuitionistic Fuzzy Valued Neutrosophic Sets: A Spatial
Multi-Criteria Decision Illustration.

.- Picture Fuzzy Set–Based Approach for Classification.

.- On admisible interval orders and partial metrics on discrete fuzzy numbers.

.- Fuzzy and multivalued logic.

.- Optimizing de Finetti’s Coherence: a Complexity Analysis.

.- On the complexity of the logics of strongly perfect MTL-algebras and
related systems.

.- Quantum-Inspired Fuzzy Committee Optimization for Blockchain
Consensus.

.- Ideally Exact Categories, Varieties of Universal Algebras and
Multi-Valued Logics.

.- Fuzzy Rule-Based Approach for Weighting Artificial Experts involved
in a Multi-Criteria Group Decision-Making Problem.

.- Functors between Fuzzy Varieties.

.- Uncertainty-Aware Graph Integration: A Fuzzy Logic Approach with
Comparative Analysis.

.- On Veracity Handling in Document Stores: A Novel Technique Based on L-graded Logic Running on the J-CO Framework.

.- A Max–Min Neural Network Model for Propositional Fuzzy Logic.

.- Fuzzy and multivalued logic.

.- An Engineering Methodology for Verifying Compliance with the EU AI
Act in Industrial AI Systems.

.- Neural Networks for Non-Convex Lattice Geometry: Extending Stoka’s
Theory with Machine Learning Application to Financial Risk and
Economic Forecasting.

.- Multi-Objective Optimization and Machine Learning Framework for
Tax Risk Management: Theory and Applications.

.- Explainable Uncertainty Quantification for Wastewater Treatment
Energy Prediction via Interval Type-2 Neuro-Fuzzy System.

.- Constraint-Based Reliability Estimation in Sparse and Irregular Time
Series.

.- Automatic Assessment of Node Compromise Risks in Critical
Infrastructures via a Multi-Stage Uncertainty Reduction Model using
LLMs.

.- On Counterfactual Explanations and Adversarial Examples for
Set-Valued Classifiers.

.- Comparative reversal learning reveals rigid adaptation in LLMs under
non-stationary uncertainty .

.- FIRE: Fuzzy Information for Reconstructing Events.

.- Leveraging Causal Graphs to Improve LLM-Based Causal Reasoning:
an Empirical Study.

.- Uncertainty Aware Contextual Recommendation under Possible Worlds
Semantics.