@inproceedings{6eea44c2824b47b7869b690de3183655,
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",
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",
pages = "713--718",
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",
}