Bingjiao Fan

TL;DR: A couple of double-quantitative decision-theoretic rough fuzzy set (Dq-DTRFS) models based on logical conjunction and logical disjunction operation are proposed and a comparative analysis using two non-rough set based methods is offered.

TL;DR: A framework of distance-based double-quantitative rough fuzzy set (Db-Dq-RFS) with logic operation is proposed by forming a distance- based fuzzy similarity relation in an information system with continuous data to simultaneously solve the two limitations of the classical rough set model.

TL;DR: An experimental evaluation on five data sets downloaded from the University of California-Irvine databases shows the feasibility and effectiveness of the attribute-oriented multi-level cognitive concept learning method.

TL;DR: Two kinds of consistency levels are introduced from the perspective of double quantification in an ordered information system, namely relative quantitative consistency level and absolute quantitative consistencylevel.

TL;DR: This paper investigates the uncertainty measure of the four disjoint regions in Dq-DTRS models by introducing a fuzziness formula for rough set, and describes the changing regularities of fuzziness of disjointed regions inDqI-D TRS model and DqII-DtrS model along with the variation of two parameters.