Prediction of Air Pollution of Boushehr City Using Data Mining

Author

Sahafizadeh, Ebrahim ; Ahmadi, Esmail

Author_Institution

Comput. Dept., Payame Noor Univ. (PNU), Boushehr, Iran

fYear

2009

fDate

28-30 Dec. 2009

Firstpage

33

Lastpage

36

Abstract

Data mining is the discovery of interesting, unexpected or valuable structures in large datasets. In this paper we use data mining technique to predict dusty days of Boushehr city as a factor of air pollution by using the data of 53 years from 1951 to 2003. We export decision rule from this data by using the air pressure, humidity and dusty days of January, February and March of each year and we describe the relation between dusty days of other future month and this first three month feature.

Keywords

air pollution; data analysis; data mining; decision trees; environmental science computing; knowledge based systems; Boushehr city; air pollution; air pressure; data mining; decision rule; dusty day prediction; humidity; Air pollution; Atmospheric measurements; Cities and towns; Clustering algorithms; Data mining; Decision trees; Humidity; Machine learning algorithms; Pressing; Sea measurements; K-Mean; air pollution; clustering; data mining; decision tree;

fLanguage

English

Publisher

ieee

Conference_Titel

Environmental and Computer Science, 2009. ICECS '09. Second International Conference on

Conference_Location

Dubai

Print_ISBN

978-0-7695-3937-9

Electronic_ISBN

978-1-4244-5591-1

Type

conf

DOI

10.1109/ICECS.2009.18

Filename

5383559