By Topic

Evaluation of Water Security by Data Mining Techniques Based on Rough Set

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Wang Hong ; Productivity Res. Center, Heilongjiang Univ., Harbin

As the rapid development of economy, increased population and lagged water conservancy, a series of civic ecological environment problems have arisen, for example, water shortage, water pollution, ecological deteriorate, which influences the sustainable development of economy. This paper studied on evaluation of water security. An improved classification algorithm by attribute importance is provided. Attributes are reduced by rough set theory, redundant attributes are removed and the core attributes are gained. When building the decision tree through the improved algorithm, the current node was chosen from the core attributes of the simplified decision table and decision tree splitting is according to the importance degree of attribute so as to reduce computation and gain relative simple classification rules. An example of water security evaluation is given to validate the improved algorithm. The results show that the method is effective. The research lays a foundation for further study on water security evaluation.

Published in:

Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on

Date of Conference:

21-22 Dec. 2008