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International Journal of Approximate Reasoning, Volume 156

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Volume 156, May 2023

Special Issue on Uncertainty, Heterogeneity, Reliability and Explainability in AI.

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  - https://dblp.org/rec/journals/ijar/GrinaEL23
Fares Grina, Zied Elouedi, Eric Lefevre:
Re-sampling of multi-class imbalanced data using belief function theory and ensemble learning. 1-15

Rough sets and granular computing

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  - journals/ijar/JainS23
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Pankhuri Jain, Tanmoy Som:
Multigranular rough set model based on robust intuitionistic fuzzy covering with application to feature selection. 16-37

Inconsistency

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John Grant, Anthony Hunter:
Semantic inconsistency measures using 3-valued logics. 38-60

Aggregation operators

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  - journals/ijar/Dan23
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Yexing Dan:
A unified way to studies of t-seminorms, t-semiconorms and semi-uninorms on a complete lattice in terms of behaviour operations. 61-76

Special Issue on Recent advances and trends in concept lattices and their applications.

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Keyi Guo, Jinhai Li, Xiao Zhang:
Notes on the improvement of concept-cognitive learning accuracy. 77-96

Rough sets and granular computing

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  - journals/ijar/ZhengQC23
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Keyin Zheng, Yuhua Qian, Honghong Cheng:
How to describe the spatial near-far relations among concepts? 97-113

Imprecise data

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  - journals/ijar/TretiakF23
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Krasymyr Tretiak, Scott Ferson:
Should data ever be thrown away? Pooling interval-censored data sets with different precision. 114-133

Special Issue on Uncertainty, Heterogeneity, Reliability and Explainability in AI.

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Serena Doria:
Coherent conditional previsions with respect to inner and outer Hausdorff measures to represent conscious and unconscious human brain activity. 134-146

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