Titlebook: Rough Sets and Knowledge Technology; 7th International Co Tianrui Li,Hung Son Nguyen,Hong Yu Conference proceedings 2012 Springer-Verlag Be

Infelicity

Muffle

Classification and Decision Based on Parallel Reducts and ,-Rough Sets reducts and .-rough sets are discussed. Unlike Pawlak rough sets or other rough set models, there may be many benchmarks for classifying(deciding). Three strategies for classifying(deciding) are proposed, including specific decision subsystem, decision subsystem selected randomly and deciding by a

Restenosis

Evidential Clustering or Rough Clustering: The Choice Is Yoursnce, Fuzzy and Rough variations of a popular K-means algorithm are proposed to obtain non-crisp clustering solutions..An Evidential c-means proposed by Masson and Denoeux [6] in the theoretical framework of belief functions uses Fuzzy c-means (FCM) to build upon basic belief assignments to determine

嘲弄

擴(kuò)大

Incremental Rules Induction Based on Rule Layerses two inequalities for accuracy and coverage. The proposed method classifies a set of formulae into three layers: rule layer, subrule layer and non-rule layer by using the inequalities obtained. Then, subrule layer plays a central role in updating rules. The proposed method was evaluated on a datas

梯田

Optimization of Inhibitory Decision Rules Relative to Length and Coverage that have on the right-hand side a relation “attribute = value”, inhibitory rules have a relation “attribute ≠ value” on the right-hand side. The considered algorithms are based on extensions of dynamic programming.

Arthr-

Optimistic Multi-Granulation Fuzzy Rough Set Model Based on Triangular Normnulation .-fuzzy lower and upper approximation operators in the generalized .-fuzzy approximation space. It is obvious that the generalize .-fuzzy lower and upper approximation operators defined on (.,.) are obtained as a special case of these operators. The main properties of the .-fuzzy lower and upper approximation operators are also studied.

NIL

Upper Approximation Reduction Based on Intuitionistic Fuzzy , Equivalence Information Systemsted, and the judgement theorems and discernibility matrices are obtained in intuitionistic fuzzy . equivalence information systems. An example illustrates the validity of the approach, and shows that it is an efficient tool for knowledge discovery in intuitionistic fuzzy . equivalence information systems.

杠桿

CARE

0302-9743 ational Conference on Rough Sets and Knowledge Technology, RSKT 2012, held in Chengdu, China during August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 63 revised papers (including 42 regular and 21 short papers) were carefully reviewed and selected