Comparison of the probabilistic approximate classification and the fuzzy set model
Fuzzy Sets and Systems
A decision-theoretic roguth set model
Methodologies for intelligent systems, 5
Variable precision rough set model
Journal of Computer and System Sciences
Advances in the Dempster-Shafer theory of evidence
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Inclusion degree: a perspetive on measures for rough set data analysis
Information Sciences—Informatics and Computer Science: An International Journal
Variable Precision Rough Sets with Asymmetric Bounds
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
Granular computing, rough entropy and object extraction
Pattern Recognition Letters
Topological approaches to covering rough sets
Information Sciences: an International Journal
Consistency measure, inclusion degree and fuzzy measure in decision tables
Fuzzy Sets and Systems
Parameterized rough set model using rough membership and Bayesian confirmation measures
International Journal of Approximate Reasoning
Editorial: Probabilistic rough sets: Approximations, decision-makings, and applications
International Journal of Approximate Reasoning
Probabilistic rough set approximations
International Journal of Approximate Reasoning
Probabilistic approach to rough sets
International Journal of Approximate Reasoning
Variable precision rough set for group decision-making: An application
International Journal of Approximate Reasoning
Modeling of High Quality Granules
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Granulations Based on Semantics of Rough Logical Formulas and Its Reasoning
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Variable-precision dominance-based rough set approach and attribute reduction
International Journal of Approximate Reasoning
A new customized document categorization scheme using rough membership
Applied Soft Computing
Adapted variable precision rough set approach for EEG analysis
Artificial Intelligence in Medicine
The investigation of the Bayesian rough set model
International Journal of Approximate Reasoning
A variable precision rough set approach to the remote sensing land use/cover classification
Computers & Geosciences
The superiority of three-way decisions in probabilistic rough set models
Information Sciences: an International Journal
Determination of the threshold value β of variable precision rough set by fuzzy algorithms
International Journal of Approximate Reasoning
Applying variable precision rough set model for clustering student suffering study's anxiety
Expert Systems with Applications: An International Journal
Modeling rough granular computing based on approximation spaces
Information Sciences: an International Journal
Comparative study of variable precision rough set model and graded rough set model
International Journal of Approximate Reasoning
β-Interval attribute reduction in variable precision rough set model
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on advances in computational intelligence and bioinformatics
Dominance-based rough set model in intuitionistic fuzzy information systems
Knowledge-Based Systems
Bayesian rough set model: A further investigation
International Journal of Approximate Reasoning
Graded rough set model based on two universes and its properties
Knowledge-Based Systems
A general frame for intuitionistic fuzzy rough sets
Information Sciences: an International Journal
Fundamenta Informaticae - Advances in Rough Set Theory
Minimum cost attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Rough set model based on formal concept analysis
Information Sciences: an International Journal
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
International Journal of Approximate Reasoning
Approximation operators on complete completely distributive lattices
Information Sciences: an International Journal
Building the fundamentals of granular computing: A principle of justifiable granularity
Applied Soft Computing
Analyzing uncertainties of probabilistic rough set regions with game-theoretic rough sets
International Journal of Approximate Reasoning
Incorporating logistic regression to decision-theoretic rough sets for classifications
International Journal of Approximate Reasoning
Multigranulation decision-theoretic rough sets
International Journal of Approximate Reasoning
Multi-class decision-theoretic rough sets
International Journal of Approximate Reasoning
An automatic method to determine the number of clusters using decision-theoretic rough set
International Journal of Approximate Reasoning
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Because precision and grade act as fundamental quantitative information in approximation space, they are used in relative and absolute quantifications, respectively. At present, the double quantification regarding precision and grade is a novel and valuable subject, but quantitative information fusion has become a key problem. Thus, this paper constructs the double-quantitative approximation space of precision and grade (PG-Approx-Space) and tackles the fusion problem using normal logical operations. It further conducts double-quantification studies on granular computing and rough set models. (1) First, for quantitative information organization and storage, we construct space and plane forms of PG-Approx-Space using the Cartesian product, and for quantitative information extraction and fusion, we establish semantics construction and semantics granules of PG-Approx-Space. (2) Second, by granular computing, we investigate three primary granular issues: quantitative semantics, complete system and optimal calculation. Accordingly, six types of fundamental granules are proposed based on the semantic, microscopic and macroscopic descriptions; their semantics, forms, structures, calculations and relationships are studied, and the granular hierarchical structure is achieved. (3) Finally, we investigate rough set models in PG-Approx-Space. Accordingly, model regions are proposed by developing the classical regions, model expansion is systematically analyzed, some models are constructed as their structures are obtained, and a concrete model is provided. Based on the quantitative information architecture, this paper systematically conducts and investigates double quantification and establishes a fundamental and general exploration framework.