Association Rules of Data Mining for the Characteristic Analysis of Subbasins of a River | Zendy

Kirti Malhotra | Zendy; Harshwin Venugopal | Zendy

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Association Rules of Data Mining for the Characteristic Analysis of Subbasins of a River

Author(s) -

Kirti Malhotra,

Harshwin Venugopal

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/3284-4473

Subject(s) - evapotranspiration , drainage basin , association rule learning , homogeneous , computer science , hydrology (agriculture) , precipitation , structural basin , cloud cover , association (psychology) , cover (algebra) , data mining , environmental science , cloud computing , geology , meteorology , cartography , geography , geomorphology , mathematics , mechanical engineering , ecology , philosophy , geotechnical engineering , epistemology , combinatorics , engineering , biology , operating system

sub basins of a river are not hydrologically homogeneous, because of their location, drainage pattern, precipitation and other characteristics. The present study is a new approach for developing relationships between different hydrological parameters such as cloud cover, potential evapotranspiration (PET), Reference Crop Evapotranspiration (RCET), vapor pressure, temperature, precipitation and discharge of different sub basins. The study considers the application of association rules of data mining for 8 sub basins of a river in south India. An attempt is also made to check whether the developed association rules in the data hyperspace have any physical meaning or not. The generated association rules indicate there is hydrological homogeneity between some sub basins while others are hydrologically heterogeneous.

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