Title :
Meteorological Data Analyze Base on K-means Algorithm
Author :
Jinghua, Huang ; Zhenchong, Wang ; Mei, Yuan ; Youwen, Bao
Author_Institution :
Sch. of Mech., Electron. & Inf. Eng., China Univ. of Min. & Technol., Beijing, China
Abstract :
The paper proposed a clustering method of decade observation data based on k-means algorithm, which adjusted the weight influence to similarity function by the missing values handling and scaling of range fields. This paper discussed the way to select initial cluster centers and the process of calculating cluster centers and assigning records to clusters. The test indicated the k-means algorithm had effective clustering result.
Keywords :
data analysis; meteorology; statistical analysis; cluster centers; decade observation data; k-means algorithm; meteorological data analysis; missing values handling; range fields scaling; similarity function; Algorithm design and analysis; Clustering algorithms; Clustering methods; Data analysis; Euclidean distance; Iterative algorithms; Machine learning algorithms; Meteorology; Partitioning algorithms; Weather forecasting; clustering; k-means algorithm; meteorological data;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.164
