Results 31 to 40 of about 758 (175)
Sampling aspects of rough set theory [PDF]
, 2004 Rough Set Theory (RST) originated as an approach to approximating a given set, but has found its main applications in the statistical domain of classification problems.
Bruce Curry, Curry, Bruce
core +1 more source
Improving airline service quality based on rough set theory and flow graphs [PDF]
, 2016 This study differs from previous studies by applying multivariate statistical analysis and multi-criterion decision-making methods to the improvement of service quality.
James J. H. Liou; Yen-Ching Chuang; Chao-Che Hsu
core +1 more source
IEEE Access, 2020 Attribute reduction is a challenging issue in intelligent manufacturing. Existing methods are mainly based on rough set theory (RST) focusing on symbolic and discrete values.
Zhiwen Zhang +4 more
doaj +1 more source
New Measures of Uncertainty for Interval-Valued Data With Application to Attribute Reduction
IEEE Access, 2022 Uncertainty measurement (UM) gives a brand-new perspective on attribute reduction in an information system (IS). Interval-valued data is a kind of very vital data in rough set theory (RST).
Lulu Li
doaj +1 more source
Knowledge discovery in marketing: an approach through rough-set theory [PDF]
, 2001 Rough set theory (RST) involves techniques for knowledge discovery or data mining. RST is typically applied within decision tables and offers an alternative to more conventional techniques for classification and rule induction.
Beynon, Malcolm James +2 more
core +1 more source
Rough set theory with discriminant analysis in analyzing electricity loads [PDF]
, 2020 [[abstract]]With the ability to deal with both numeric and nominal information, rough set theory (RST), which can express knowledge in a rule-based form, has been one of the most important techniques in data analysis.
白炳豐 , Pai, PF
core +2 more sources
Dimensionality reduction method for hyperspectral image analysis based on rough set theory
European Journal of Remote Sensing, 2020 High-dimensional features often cause computational complexity and dimensionality curse. Feature selection and feature extraction are the two mainstream methods for dimensionality reduction.
Zhenhua Wang +5 more
doaj +1 more source
An Intelligent Approach of Rough Set in Knowledge Discovery Databases [PDF]
, 2007 Knowledge Discovery in Databases (KDD) has evolved into an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering (or extracting) interesting and previously unknown ...
Pradip K. Das +2 more
core +1 more source
EnergiesThis research was carried out to compare selected forecasting methods, such as the following: Artificial Neural Networks (ANNs), Classification and Regression Trees (CARTs), Chi-squared Automatic Interaction Detector (CHAID), Fuzzy Logic Toolbox (FUZZY),
Joanna Piotrowska-Woroniak +3 more
doaj +1 more source
A Metaphor for Rough Set Theory: Modular Arithmetic [PDF]
, 2018 © Springer Nature Switzerland AG 20118. Technically put, a metaphor is a conceptual mapping between two domains, which allows one to better understand the target domain; as Lakoff and Núñes put it, the main function of a metaphor is to allow us to reason
Wolski, Marcin +3 more
core +1 more source