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Isolation-based hyperbox granular classification computing

Journal of Algorithms & Computational Technology, 2017
Bottom-up and top-down are two main computing models in granular computing by which the granule set including granules with different granularities. The top-down hyperbox granular computing classification algorithm based on isolation, or IHBGrC for short,
Hongbing Liu, Fan Zhang, Ran Li, Chang-an Wu   +3 more
doaj   +2 more sources

A Granular Computing Method for Economic Dispatch Problems With Valve-Point Effects

IEEE Access, 2019
This paper presents a granular computing method (GrC) for the economic dispatch (ED) problems with valve-point effects to reduce the computational dimension and improve the solving accuracy.
Xueping Li, Anyi Li, Zhigang Lu
doaj   +1 more source

A fuzzy concept-cognitive learning method integrating fuzzy coverage

Nantong Daxue xuebao. Ziran kexue ban
Concept-cognitive learning is an emerging interdisciplinary research area that aims to continuously learn new knowledge by imitating the human cognitive process.
WU Yuqing；LIN Yidong；LIANG Taoju
doaj   +1 more source

Training dictionary by granular computing with L∞-norm for patch granule–based image denoising

Journal of Algorithms & Computational Technology, 2018
Considering the objects by different granularity reflects the recognition common law of people, granular computing embodies the transformation between different granularity spaces.
Hongbing Liu, Gengyi Liu, Xuewen Ma, Daohua Liu   +3 more
doaj   +1 more source

Granular Computing Based Ontology Learning Model and Its Applications

Cybernetics and Information Technologies, 2015
The cores of granular computing are the granule, the granule layer and the granule structure. In this paper the concepts “Ontology granule” and “Compatible granule” were defined, applying the granular computing ideas and an ontology model, an Ontology ...
Yan Hongcan, Zhang Feng, Liu Baoxiang
doaj   +1 more source

Random Fuzzy Clustering Granular Hyperplane Classifier

IEEE Access, 2020
Granular computing is a method of studying human intelligent information processing, which has advantage of knowledge discovery. In this paper, we convert a classification problem of sample space into a classification problem of fuzzy clustering granular
Wei Li, Kaiqiang Zhang, Yumin Chen, Chao Tang, Xiaoyu Ma, Youmeng Luo   +5 more
doaj   +1 more source

Nonparametric Hyperbox Granular Computing Classification Algorithms

Information, 2019
Parametric granular computing classification algorithms lead to difficulties in terms of parameter selection, the multiple performance times of algorithms, and increased algorithm complexity in comparison with nonparametric algorithms.
Hongbing Liu, Xiaoyu Diao, Huaping Guo
doaj   +1 more source

Prediction and analysis of time series data based on granular computing. [PDF]

Front Comput Neurosci, 2023
Yin Y.
europepmc   +1 more source

Research on Embedded Multifunctional Data Mining Technology Based on Granular Computing. [PDF]

Comput Intell Neurosci, 2022
Li J, Tian X.
europepmc   +1 more source

On SI2-convergence in T0-spaces

Open Mathematics
Recently, Shen et al. showed that the SI2-topology on a T0{T}_{0}-space can be described completely in terms of SI2-convergence, and the SI2-convergence is topological whenever the given space is SI2-continuous.
Yang Yi, Xu Xiaoquan
doaj   +1 more source