Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Rough mereological foundations for design, analysis, synthesis, and control in distributed systems
Information Sciences: an International Journal - From rough sets to soft computing
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Knowledge-Based Clustering: From Data to Information Granules
Knowledge-Based Clustering: From Data to Information Granules
Interpretation of clusters in the framework of shadowed sets
Pattern Recognition Letters
Fuzzy Systems Engineering: Toward Human-Centric Computing
Fuzzy Systems Engineering: Toward Human-Centric Computing
Human-Centric Information Processing Through Granular Modelling
Human-Centric Information Processing Through Granular Modelling
Design of interval type-2 fuzzy models through optimal granularity allocation
Applied Soft Computing
A review on the design and optimization of interval type-2 fuzzy controllers
Applied Soft Computing
Shadowed sets: representing and processing fuzzy sets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Hierarchical description of uncertain information
Information Sciences: an International Journal
Information Sciences: an International Journal
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The study introduces and discusses a principle of justifiable granularity, which supports a coherent way of designing information granules in presence of experimental evidence (either of numerical or granular character). The term ''justifiable'' pertains to the construction of the information granule, which is formed in such a way that it is (a) highly legitimate (justified) in light of the experimental evidence, and (b) specific enough meaning it comes with a well-articulated semantics (meaning). The design process associates with a well-defined optimization problem with the two requirements of experimental justification and specificity. A series of experiments is provided as well as a number of constructs carried for various formalisms of information granules (intervals, fuzzy sets, rough sets, and shadowed sets) are discussed as well.