In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3559-3565

Second-order natural nearest neighbors and multi-clusters merge density peaks clustering algorithm

Zhang Zidan
Xu Hua
Yang Chongyang
School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2023.04.0162

Abstract

The DPC algorithm identifies cluster centers based on local density and relative distance, ignoring the influence of the sample environment on the sample point density, so it is not easy to find cluster centers in low-density areas. The single-step allocation strategy of the DPC algorithm has poor fault tolerance, and once a sample point allocation error occurs, it will lead to a series of sample point allocation errors in the follow-up. To solve the above problems, this paper proposed a density peak clustering algorithm(TNMM-DPC) based on second-order natural nearest neighbor and multi-cluster merging. Firstly, it introduced the concept of second-order natural neighbor and considered the density of the sample point and the environment of the sample point at the same time, it redefined the local density of the sample point to reduce the influence of cluster density on the selection of cluster center. Secondly, it defined the core point set to select the initial micro clusters, and allocated the sample points according to the correlation degree between the sample points and the micro clusters. Finally, it introduced the concept of neighbor boundary point set to merge the adjacent subclusters to obtain the final clustering results, avoiding the cascade effect of allocation errors. This paper compared TNMM-DPC algorithm with DPC and its improved algorithm on the artificial dataset and the UCI dataset, and the experimental results show that the TNMM-DPC algorithm can solve the problems existing in the DPC algorithm and can effectively cluster the artificial dataset and UCI dataset.

Foundation Support

国家自然基金青年基金资助项目(62106088)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.04.0162
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Algorithm Research & Explore
Pages: 3559-3565
Serial Number: 1001-3695(2023)12-006-3559-07

Publish History

[2023-07-05] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

张紫丹, 徐华, 杨重阳. 二阶自然最近邻和多簇合并的密度峰值聚类算法 [J]. 计算机应用研究, 2023, 40 (12): 3559-3565. (Zhang Zidan, Xu Hua, Yang Chongyang. Second-order natural nearest neighbors and multi-clusters merge density peaks clustering algorithm [J]. Application Research of Computers, 2023, 40 (12): 3559-3565. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)