模糊c均值聚类与模糊聚类减法在城市空气污染中的比较

2010 20th International Conference on Electronics Communications and Computers (CONIELECOMP) Pub Date : 2010-04-01 DOI:10.1109/CONIELECOMP.2010.5440772

José Iván Collazo-Cuevas, M. Aceves-Fernández, E. G. Hurtado, J. Ortega, A. Sotomayor-Olmedo, M. Delgado-Rosas

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引用次数: 16

摘要

聚类通常与分类问题有关。在这篇贡献中，实现了聚类估计方法作为模糊模型识别算法的基础。对模糊c均值聚类和模糊聚类减法聚类两种不同的聚类技术进行了比较。此外，本文还介绍了在模拟英格兰西北部利物浦城市空气污染中温度、湿度和PM10浓度关系中的应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparison between Fuzzy C-means clustering and Fuzzy Clustering Subtractive in urban air pollution

Clustering is generally associated with classification problem. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. A comparison between two different clustering techniques is presented, Fuzzy C-means clustering and Fuzzy Clustering Subtractive. Also, an application in modeling the relationship between temperature, humidity and PM10 concentration in urban air pollution in Liverpool at northwest of England is presented.

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来源期刊

2010 20th International Conference on Electronics Communications and Computers (CONIELECOMP)

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