Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 1
94-98

Research on multiple distance clustering based on multi-objective evolutionary algorithm

Liu Cong
Wan Xiuhua
Peng Dunlu
Wu Chunxue
School of Optical-Electrical & Computer Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2017.06.0658

Abstract

Traditional clustering algorithms often based on a single distance metric, and how to integrate multivariate metrics is a key challenge in clustering algorithms. This paper proposed a multiobjective evolutionary multiple distance measure clustering based on multi-objective evolutionary algorithm. It used the Euclidean distance and Path distance to design the actual framework. Firstly, the framework used the two distance measures to preprocess the classes, and then combined the prepolymerization results to reduce the size of the problem. Secondly, it used the multi-objective evolutionary algorithm to cluster in two distance spaces in parallel. In the design of multi-objective evolutionary algorithm, chromosomes using real-tag coding, it designed and two fitness functions based on two distance measures to evaluate the chromosomes. Finally, compared MOMDC to several other classic algorithms in the data set. Experiments show that the framework can achieve good results for different distributed data sets.

Foundation Support

国家自然科学基金资助项目(61703278)
上海重点科技攻关项目(14511107902)
上海智能家居大规模物联共性技术工程中心项目(GCZX14014)
上海市一流学科建设项目(XTKX2012)
沪江基金研究基地专项资助项目(C14001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.06.0658
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 1
Section: Algorithm Research & Explore
Pages: 94-98
Serial Number: 1001-3695(2019)01-021-0094-05

Publish History

[2019-01-05] Printed Article

Cite This Article

刘丛, 万秀华, 彭敦陆, 等. 基于多目标进化算法的多距离聚类研究 [J]. 计算机应用研究, 2019, 36 (1): 94-98. (Liu Cong, Wan Xiuhua, Peng Dunlu, et al. Research on multiple distance clustering based on multi-objective evolutionary algorithm [J]. Application Research of Computers, 2019, 36 (1): 94-98. )

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.

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