DocumentCode
3395105
Title
Estimating the availability of sunshine using data mining techniques
Author
Mayilvahanan, M. ; Sabitha, M.
Author_Institution
Dept. of Comput. Sci., PSG Coll. of Arts & Sci., Coimbatore, India
fYear
2013
fDate
4-6 Jan. 2013
Firstpage
1
Lastpage
4
Abstract
The daily temperature values of a city or place acts as data for prediction of rainfall, energy calculation etc. There are weather stations available which records the weather of almost all the region in the earth. The weather data acquired in these stations are raw data and found in abundance. The data mining techniques can be applied to these raw data to acquire meaningful patterns out of it, which can be used to predict rainfall, solar energy availability etc. This paper deals with estimating the temperature values of four cities in Tamil Nadu, South India namely Chennai, Coimbatore, Madurai and Kanyakumari. The paper also illustrates the use of data mining technique- Clustering algorithms Simple k-Means and Expectation Maximization algorithm to compare the availability of sun shine in the above mentioned cities, this facilitates for estimation of solar energy to be acquired in these cities.
Keywords
data mining; estimation theory; expectation-maximisation algorithm; geophysics computing; pattern clustering; weather forecasting; Chennai; Coimbatore; Earth; Kanyakumari; Madurai; South India; Tamil Nadu; city daily temperature values; clustering algorithms; data mining; energy calculation; expectation maximization algorithm; rainfall prediction; simple k-means; sunshine availability estimation; temperature value estimation; weather stations; Cities and towns; Clustering algorithms; Data mining; Meteorology; Solar energy; Solar radiation; Temperature distribution; Clustering; Data Mining; Expectation Maximization; Simple K-Means; Solar energy; Weather Data;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communication and Informatics (ICCCI), 2013 International Conference on
Conference_Location
Coimbatore
Print_ISBN
978-1-4673-2906-4
Type
conf
DOI
10.1109/ICCCI.2013.6466298
Filename
6466298
Link To Document