A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System

A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System

This study proposes a novel method to calculate the density of the data points based on K-nearest neighbors and Shannon entropy. A variant of tissue-like P systems with active membranes is introduced to realize the clustering process. The new variant of tissue-like P systems can improve the efficien...

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Main Authors: Zhenni Jiang, Xiyu Liu, Minghe Sun
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/1713801
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spelling doaj-4cc2d331c24747ab81a82f17a55295b72020-11-25T00:37:47ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/17138011713801A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P SystemZhenni Jiang0Xiyu Liu1Minghe Sun2Business School, Shandong Normal University, Jinan, ChinaBusiness School, Shandong Normal University, Jinan, ChinaBusiness School, University of Texas at San Antonio, San Antonio, USAThis study proposes a novel method to calculate the density of the data points based on K-nearest neighbors and Shannon entropy. A variant of tissue-like P systems with active membranes is introduced to realize the clustering process. The new variant of tissue-like P systems can improve the efficiency of the algorithm and reduce the computation complexity. Finally, experimental results on synthetic and real-world datasets show that the new method is more effective than the other state-of-the-art clustering methods.http://dx.doi.org/10.1155/2019/1713801
collection DOAJ
language English
format Article
sources DOAJ
author Zhenni Jiang
Xiyu Liu
Minghe Sun
spellingShingle Zhenni Jiang
Xiyu Liu
Minghe Sun
A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
Mathematical Problems in Engineering
author_facet Zhenni Jiang
Xiyu Liu
Minghe Sun
author_sort Zhenni Jiang
title A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
title_short A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
title_full A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
title_fullStr A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
title_full_unstemmed A Density Peak Clustering Algorithm Based on the K-Nearest Shannon Entropy and Tissue-Like P System
title_sort density peak clustering algorithm based on the k-nearest shannon entropy and tissue-like p system
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2019-01-01
description This study proposes a novel method to calculate the density of the data points based on K-nearest neighbors and Shannon entropy. A variant of tissue-like P systems with active membranes is introduced to realize the clustering process. The new variant of tissue-like P systems can improve the efficiency of the algorithm and reduce the computation complexity. Finally, experimental results on synthetic and real-world datasets show that the new method is more effective than the other state-of-the-art clustering methods.
url http://dx.doi.org/10.1155/2019/1713801
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AT xiyuliu adensitypeakclusteringalgorithmbasedontheknearestshannonentropyandtissuelikepsystem
AT minghesun adensitypeakclusteringalgorithmbasedontheknearestshannonentropyandtissuelikepsystem
AT zhennijiang densitypeakclusteringalgorithmbasedontheknearestshannonentropyandtissuelikepsystem
AT xiyuliu densitypeakclusteringalgorithmbasedontheknearestshannonentropyandtissuelikepsystem
AT minghesun densitypeakclusteringalgorithmbasedontheknearestshannonentropyandtissuelikepsystem
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