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Fuzzy logic water quality
Date:4/17/2008

eir values may not be related. Just as apples and oranges are different but all represent the quality of fruitiness, so biochemical oxygen demand and chemical concentrations, for instance, may represent a particular aspect of water quality and so can be combined through fuzzy analysis.

In the present study, the fuzzy analysis of the river Kerayong reveals that it is highly polluted river with a very low water quality index, despite superficial analysis of individual parameters are necessary. This suggests that the quality of life of those relying on the river as a freshwater source could be improved considerably by addressing the individual pollution problems.

"We recommend further studies on data mining capabilities of the Fuzzy Inference System using more than six indicators of water quality," the researchers conclude.


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Contact: Ramani Bai Gopinath
ramanibai@um.edu.my
Inderscience Publishers
Source:Eurekalert

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