Comprehensive assessment of groundwater quality in Minqin Basin based on T-S Fuzzy Neural Network |
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DOI:10.7606/j.issn.1000-7601.2013.01.35 |
Key Words: T-S Fuzzy Neural Network model Support Vector Machines groundwater quality assessment Minqin Basin |
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Abstract: |
In order to find out the variation of groundwater quality of Minqin basin in Shiyang River Valley in recent 25 years and to provid
e the decision-making reference for rational exploitation of local water resources and eco-environmental protection, T-S Fuzzy Neural Network model was applied to the comprehensive assessment of groundwater quality in the year of 1983, 1990, 2000 and 2008, and the Support Vector Machines (SVM) model was applied to test the results. The results showed that the overall groundwater quality of Minqin Basin was poor and it was overall better in the southern region than in the northern region. Except for the area surrounding Hongyashan reservoir, the groundwater quality of more than 80% regions was poorly achieved grade Ⅴ. The groundwater quality of partial wells at the edge of deserts, such as No. 141, 147, 156 and 168, showed a improving trend. The results of the two models were generally concordant, but the T-S Fuzzy Neural Network model exhibited a fast convergence, therefore it can be effectively applied to the comprehensive assessment of groundwater quality. |
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