DCC: a framework for dynamic granular clustering

Article Properties
Cite
Peters, Georg, and Richard Weber. “DCC: A Framework for Dynamic Granular Clustering”. Granular Computing, vol. 1, no. 1, 2016, pp. 1-11, https://doi.org/10.1007/s41066-015-0012-z.
Peters, G., & Weber, R. (2016). DCC: a framework for dynamic granular clustering. Granular Computing, 1(1), 1-11. https://doi.org/10.1007/s41066-015-0012-z
Peters G, Weber R. DCC: a framework for dynamic granular clustering. Granular Computing. 2016;1(1):1-11.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
Cybernetics
Information theory
Refrences
Title Journal Journal Categories Citations Publication Date
10.1109/TFUZZ.2014.2329707 IEEE Transactions on Fuzzy Systems
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 2015
Soft clustering – Fuzzy and rough approaches and their extensions and derivatives International Journal of Approximate Reasoning
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 104 2013
10.1109/TSMCB.2011.2170067 2012
Dynamic clustering with soft computing

 WIREs Data Mining and Knowledge Discovery
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 7 2012
A survey on learning from data streams: current and future trends Progress in Artificial Intelligence
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 53 2012
Citations
Title Journal Journal Categories Citations Publication Date
INCM: neutrosophic c-means clustering algorithm for interval-valued data Granular Computing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Science (General): Cybernetics: Information theory
 1 2024
Credal-based fuzzy number data clustering Granular Computing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Science (General): Cybernetics: Information theory
 13 2023
On Information Granulation via Data Filtering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study

 SN Computer Science 2023
An overview of granular computing in decision-making: Extensions, applications, and challenges Information Fusion
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 11 2023
Algebraic Structure Based Clustering Method from Granular Computing Prospective

 International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 2023
Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science98
Science: Science (General): Cybernetics: Information theory47
Technology: Mechanical engineering and machinery43
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics43
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication22
Technology: Technology (General): Industrial engineering. Management engineering: Information technology21
Technology: Engineering (General). Civil engineering (General)14
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks7
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware5
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software4
Science: Mathematics3
Technology: Mechanical engineering and machinery: Renewable energy sources2
Geography. Anthropology. Recreation: Environmental sciences2
Technology: Environmental technology. Sanitary engineering2
Science: Biology (General): Ecology2
Technology: Manufactures: Production management. Operations management2
Geography. Anthropology. Recreation: Geography (General)1
Technology: Photography1
Science: Geology1
Technology: Electrical engineering. Electronics. Nuclear engineering1
Technology: Engineering (General). Civil engineering (General): Environmental engineering1
Medicine: Public aspects of medicine1
Medicine: Internal medicine: Special situations and conditions: Industrial medicine. Industrial hygiene1
Social Sciences1
Science: Astronomy: Astrophysics1
Science: Physics1
Technology: Technology (General): Industrial engineering. Management engineering1
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry1
Science: Science (General)1
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 98 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech and was published in 2016. The most recent citation comes from a 2024 study titled INCM: neutrosophic c-means clustering algorithm for interval-valued data. This article reached its peak citation in 2017, with 29 citations. It has been cited in 35 different journals, 22% of which are open access. Among related journals, the Granular Computing cited this research the most, with 24 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year