Results 31 to 40 of about 1,694,129 (281)
Attribute Reduction with Fuzzy Weighted Neighborhood Rough Sets [PDF]
Neighborhood rough sets (NRSs) have been widely recognized as an efficient tool for solving attribute reduction problems in numerical data. In constructing neighborhood information granules, many existing extensions introduce weighting mechanisms for ...
Pham Viet Anh +4 more
doaj +1 more source
Neighborhood Rough Fuzzy Penetration Control Method with Variable Precision Based on GMAW
Considering the nonlinear, time-varying, and multivariate coupling nature of the welding process, achieving excellent control of the welding process can be challenging.
Xiaohong Xiang +7 more
doaj +1 more source
Quantitative dominance-based neighborhood rough sets via fuzzy preference relations
Dominance relations exist extensively in decision-making problems. Dominance-based neighborhood rough sets (DNRS) using fuzzy preference relations (FPRs) are presented in this article to deal with attribute reduction in the large-scale decision-making ...
Shi, Guang +5 more
core +1 more source
Rough sets meet statistics : a new view on rough set reasoning about numerical data
In this paper, we present a new view on how the concept of rough sets may be interpreted in terms of statistics and used for reasoning about numerical data.
Chris Cornelis +11 more
core +1 more source
Neighborhood Rough-Sets-Based Spatial Data Analytics
Rough Set Theory partitions a universe using single layered granulation. The equivalence classes induced by rough sets are based on discretised values. Considering the fact that the spatial data are continuous at large, discretising them may cause loss ...
Sharmila Banu K., B. K. Tripathy
core +1 more source
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Feature Selection for Multi-Label Learning Based on F-Neighborhood Rough Sets
Multi-label learning is often applied to handle complex decision tasks, and feature selection is its essential part. The relation of labels is always ignored or not enough to consider for both multi-label learning and its feature selection.
Zhixuan Deng +5 more
doaj +1 more source
Existing 3D city reconstruction via oblique photography can only produce surface models, lacking semantic information about the urban environment and the ability to incorporate all individual buildings.
Wenqiang Xu, Yongnian Zeng, Changlin Yin
doaj +1 more source
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source
Both neutrosophic sets theory and rough sets theory are emerging as powerful tool for managing uncertainty, indeterminate, incomplete and imprecise information. In this paper we develop an hybrid structure called rough neutrosophic sets and studied their
Florentin Smarandache +7 more
core +2 more sources

