Water quality evaluation entails both
randomness and fuzziness. Considering that water eutrophication evaluation involves many indices, different classifications and
interval values, fuzzy variable sets theory was developed to Lake Baiyangdian
as a study case. Taking reference to eutrophication standard of Chinese lakes
and local characteristic of Lake Baiyangdian, eutrophication degree of lake was
divided into 8 levels. Total phosphorus, total nitrogen, and CODMn were selected
as evaluation indices
in this research. Based on the measured data, index feature value matrix of
sample was built. Index weights were determined by means of pure threshold
value method. Relative membership degree of each index to each classification was calculated with relative
difference function model. Then the stability of feature value of
classification corresponding was received by the comprehensive calculation with
the relative membership degree and index weights. The results show that the
proposed models are effective tools for generating a set of realistic and
flexible optimal solutions for complicated water quality evaluation issues. It
concluded that the model was reasonable and practical.
Cite this paper
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