Title :
Based on k-Means and Fuzzy k-Means Algorithm Classification of Precipitation
Author :
Yang Lihua ; Deng Meilan
Author_Institution :
Sch. of Inf. Eng., JingDeZhen Ceremic Inst., Jingdezhen, China
Abstract :
In this paper, the author used K-means and fuzzy K-means to analyze the classification of precipitation in JingDeZhen City, and the results showed that using fuzzy k-means algorithm is a more efficient data clustering algorithm, with better value of promotion and practical application.
Keywords :
atmospheric precipitation; atmospheric techniques; fuzzy systems; geophysical signal processing; pattern classification; pattern clustering; JingDeZhen City; data clustering algorithm; fuzzy k-means algorithm; k-means algorithm; precipitation classification; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Convergence; Indexes; Iterative algorithm; Partitioning algorithms; K-means; Precipitation classification (key words); fuzzy K-means;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-8094-4
DOI :
10.1109/ISCID.2010.72
