Results 21 to 30 of about 758 (175)
Strongly Connected Components Mining Algorithm Based on k-step Search of Vertex Granule and Rough Set Theory [PDF]
Jisuanji kexue, 2022 Strong connected components (SCCs) mining is one of the classic problems in graph theory.It has practical requirements to design a serial SCCs mining algorithm with high efficiency.GRSCC algorithm can use SUB-RSCC function to discover SCCs of simple ...
CHENG Fu-hao, XU Tai-hua, CHEN Jian-jun, SONG Jing-jing, YANG Xi-bei
doaj +1 more source
Sequential Design-Space Reduction and Its Application to Hull-Form Optimization
Journal of Marine Science and Engineering, 2023 Hull-form optimization is a complex engineering problem. Owing to the several numerical simulations and complex design-performance spaces, hull-form optimization is considered an inefficient process, which makes determining the global optimum difficult ...
Zu-Yuan Liu +4 more
doaj +1 more source
An Efficient Classification Model using Fuzzy Rough Set Theory and Random Weight Neural Network [PDF]
, 2021 In the area of fuzzy rough set theory (FRST), researchers have gained much interest in handling the high-dimensional data. Rough set theory (RST) is one of the important tools used to pre-process the data and helps to obtain a better predictive model ...
Rana Aamir Raza
core +2 more sources
A scalable and effective rough set theory-based approach for big data pre-processing [PDF]
, 2020 International audienceA big challenge in the knowledge discovery process is to perform data pre-processing, specifically feature selection, on a large amount of data and high dimensional attribute set.
Lebbah, Mustapha +7 more
core +1 more source
Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities [PDF]
International Journal of Computational Intelligence Systems, 2011 Due to the implicit characteristics of learning disabilities (LDs), the diagnosis of students with learning disabilities has long been a difficult issue.
Tung-Kuang Wu +4 more
doaj +1 more source
Parkinson’s disease development prediction by c-granule computing compared to different AI methods
Journal of Information and Telecommunication, 2020 Both rough set theory (RST) and fuzzy rough set theory (FRST) are related to intelligent granular computing (GrC) primarily with the help of static granules.
Andrzej W. Przybyszewski +1 more
doaj +1 more source
, 2008 Rough set theory (RST), since its introduction in Pawlak (1982), continues to develop as an effective tool in classification problems and decision support. In the majority of applications using RST based methodologies, there is the construction of ‘if ..
Beynon, Malcolm James, Malcolm J. Beynon
core +1 more source
Information veins and re-sampling with rough set theory [PDF]
, 2008 Rough Set Theory (RST), since its introduction in Pawlak (1982), continues to develop as an effective tool in data mining. Within a set theoretical structure, its remit is closely concerned with the classification of objects to decision attribute values,
Benjamin Griffiths, Griffiths, Benjamin
core +1 more source
Polish Cartographical Review, 2020 Selection is a key element of the cartographic generalisation process, often being its first stage. On the other hand it is a component of other generalisation operators, such as simplification.
Fiedukowicz Anna
doaj +1 more source
Applications of Rough Sets in Big Data Analysis: An Overview
International Journal of Applied Mathematics and Computer Science, 2021 Big data, artificial intelligence and the Internet of things (IoT) are still very popular areas in current research and industrial applications.
Pięta Piotr, Szmuc Tomasz
doaj +1 more source