A data mining application on air temperature database
Küçük Resim Yok
Tarih
2004
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, a data mining application based on DBSCAN (Density Based Spatial Clustering of Applications with Noise) was carried out on air temperature database which contains daily temperature data from country wide meteorology stations in Turkey. At the end of data mining process, we obtained clusters that have similar temperature trends. These clusters have been used to categorize Turkey into regions according to climatic characteristics. Statistical methods are widely used in meteorology; however they need extreme computing power. Data mining methods provide more performance and reliability than statistical methods. © Springer-Verlag 2004.
Açıklama
Anahtar Kelimeler
Kaynak
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
3261
