A data clustering algorithm based on mussels wandering optimization

Peng Yan; Shi Yao Liu; Qi Kang; Bing Yao Huang; Meng Chu Zhou

doi:10.1109/ICNSC.2014.6819713

A data clustering algorithm based on mussels wandering optimization

Peng Yan, Shi Yao Liu, Qi Kang, Bing Yao Huang, Meng Chu Zhou

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.

Original language	English (US)
Title of host publication	Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
Publisher	IEEE Computer Society
Pages	713-718
Number of pages	6
ISBN (Print)	9781479931064
DOIs	https://doi.org/10.1109/ICNSC.2014.6819713
State	Published - Jan 1 2014
Event	11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 - Miami, FL, United States Duration: Apr 7 2014 → Apr 9 2014

Publication series

Name	Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Other

Other	11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
Country/Territory	United States
City	Miami, FL
Period	4/7/14 → 4/9/14

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Control and Systems Engineering

Keywords

clustering
data mining
mussels wandering optimization
optimization
swarm intelligence

Access to Document

10.1109/ICNSC.2014.6819713

Cite this

Yan, P., Liu, S. Y., Kang, Q., Huang, B. Y., & Zhou, M. C. (2014). A data clustering algorithm based on mussels wandering optimization. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 (pp. 713-718). [6819713] (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014). IEEE Computer Society. https://doi.org/10.1109/ICNSC.2014.6819713

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title = "A data clustering algorithm based on mussels wandering optimization",

abstract = "As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.",

keywords = "clustering, data mining, mussels wandering optimization, optimization, swarm intelligence",

author = "Peng Yan and Liu, {Shi Yao} and Qi Kang and Huang, {Bing Yao} and Zhou, {Meng Chu}",

year = "2014",

month = jan,

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doi = "10.1109/ICNSC.2014.6819713",

language = "English (US)",

isbn = "9781479931064",

series = "Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014",

publisher = "IEEE Computer Society",

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booktitle = "Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014",

address = "United States",

note = "11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 ; Conference date: 07-04-2014 Through 09-04-2014",

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Yan, P, Liu, SY, Kang, Q, Huang, BY & Zhou, MC 2014, A data clustering algorithm based on mussels wandering optimization. in Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014., 6819713, Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014, IEEE Computer Society, pp. 713-718, 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014, Miami, FL, United States, 4/7/14. https://doi.org/10.1109/ICNSC.2014.6819713

A data clustering algorithm based on mussels wandering optimization. / Yan, Peng; Liu, Shi Yao; Kang, Qi et al.
Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014. IEEE Computer Society, 2014. p. 713-718 6819713 (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A data clustering algorithm based on mussels wandering optimization

AU - Yan, Peng

AU - Liu, Shi Yao

AU - Kang, Qi

AU - Huang, Bing Yao

AU - Zhou, Meng Chu

PY - 2014/1/1

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N2 - As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.

AB - As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.

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KW - data mining

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KW - optimization

KW - swarm intelligence

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BT - Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

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Yan P, Liu SY, Kang Q, Huang BY, Zhou MC. A data clustering algorithm based on mussels wandering optimization. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014. IEEE Computer Society. 2014. p. 713-718. 6819713. (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014). doi: 10.1109/ICNSC.2014.6819713

A data clustering algorithm based on mussels wandering optimization

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All Science Journal Classification (ASJC) codes

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