Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 2
391-397

Cloud pattern clustering algorithms on big data of Internet of Things based on extracting chaotic correlation features of events

Wang Xueronga
Wan Nianhongb
a. Dept. of Teaching Work, b. School of Digital Engineering, Zhejiang Dongfang Polytechnic, Wenzhou Zhejiang 325000, China
DOI: 10.19734/j.issn.1001-3695.2020.02.0013

Abstract

Current clustering methods study data clustering problems only from one angle, it is insufficient to considerate clustering chaotic big data of Internet of Things based on cloud pattern with low clustering quality. To achieve agile, intelligent and stable clustering on big data of Internet of Things, with studying general cloud pattern description models on events of Internet of Things, general cloud pattern analysis models on chaotic correlation features of events of Internet of Things, extracting algorithms on chaotic correlation features of events of Internet of Things based on cloud pattern, correlation mining of big data of Internet of Things based on cloud pattern chaotic correlation features, improved decompositing singular value algorithms, grid coupling clustering algorithms, K-means algorithms, decision tree learning methods, methods of analysis principal components, stratification merging methods and distribution probability function, this paper designed an agile, intelligent and stable clustering algorithm on big data of Internet of Things based on chaotic correlation features of events. Finally, it carried out vali-dating experiments, and compared performance of this proposed algorithm with traditional algorithms. Experimental results show this algorithm has shorter clustering time, less error and higher agility, has better intelligence, dynamic evolution, stabi-lity than those of traditional algorithms. Therefore, this proposed algorithm achieves effective clustering on big data of events of Internet of Things with chaotic correlation features based on cloud patterns, has higher utility.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.02.0013
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 2
Section: Algorithm Research & Explore
Pages: 391-397
Serial Number: 1001-3695(2021)02-012-0391-07

Publish History

[2021-02-05] Printed Article

Cite This Article

王雪蓉, 万年红. 云模式事件混沌关联特征提取的物联网大数据聚类算法 [J]. 计算机应用研究, 2021, 38 (2): 391-397. (Wang Xuerong, Wan Nianhong. Cloud pattern clustering algorithms on big data of Internet of Things based on extracting chaotic correlation features of events [J]. Application Research of Computers, 2021, 38 (2): 391-397. )

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  • Application Research of Computers Monthly Journal
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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.

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