Titlebook: Rough Sets; International Joint Rafael Bello,Duoqian Miao,Davide Ciucci Conference proceedings 2020 Springer Nature Switzerland AG 2020 ar

沉思的魚

On Positive-Correlation-Promoting Reductsuch attributes – called positive-correlation-promoting reducts (PCP reducts in short) – using standard calculations over appropriately modified rough-set-based discernibility matrices. The proposed framework is implemented within the RoughSets R package which is widely used for the data exploration and knowledge discovery purposes.

heterodox

Similarity Based Granules called representatives and it can be useful to apply them in the approximation of an arbitrary set. A new approximation pair can be defined based on the representatives. In this paper, some very important properties are checked for this approximation pair and the system of granules.

外表讀作

Modeling Use-Oriented Attribute Importance with the Three-Way Decision Theorylist as well as a set of numerical weights of an attribute set. We then categorize attributes into different groups of importance using qualitative and quantitative analysis results. Finally, a unified model to analyze user-oriented attribute importance is constructed.

legislate

人類

Weighted Generalized Fuzzy Petri Nets and Rough Sets for Knowledge Representation and Reasoningppropriate decisions can be made. Conditional attribute values given by experts are propagated by the net at maximum speed. This is done by properly organizing the net’s work. Our approach is based on rough set theory and weighted generalized fuzzy Petri nets.

沉著

Rough Sets Meet Statistics - A New View on Rough Set Reasoning About Numerical Data events. We propose a way of choosing the optimal neighborhood size inspired by statistical theory. We also discuss possible directions for future research on the integration of rough sets and statistics.

hazard

DEAWL

Pituitary-Gland

Rough Forgetting of . of the form ., where . is a set of relations in the language signature used to specify the KB. The result of this operation is a new KB where the relations in . are removed from the KB in a principled manner resulting in a more efficient representation of the KB for different purposes. The for