To facilitate the comparative water quality assessment results, Table 5 summarizes the assessment results for three methods. The calculated MAE, RMSE and R2 are 0.292, 0.371, 0.989 for BP-ANN model, and those of WNN are 0.073, 0.091 and 0.996, indicating that WNN model has a higher accuracy. Although the BP model has a good stability shown above, the evaluating result has a relatively large difference. According to the comparison of two neural network methods, the WNN method has a higher accuracy than the BP-ANN method. The BP method requires more iteration with no guarantee of accuracy of the results for the same task. It reveals that the WNN and NMR methods are both effective for water quality assessment because the result is consistent with the actual water quality status.

Table 5

Water quality evaluation in the WNN, NMR and BP methods

YearWater quality grade
#1
#2
#3
#4
#5
WNNNMRBPWNNNMRBPWNNNMRBPWNNNMRBPWNNNMRBP
2004 IV IV III II III IV III II III III 
2005 IV IV IV II II IV IV III II III IV III II 
2006 IV IV IV IV III IV IV II 
2007 IV IV III II IV IV II III III II 
2008 IV IV III III IV IV IV IV II IV 
2009 IV IV III II IV IV IV IV III 
2010 IV IV III II IV III II II II II II IV 
2011 IV IV II III IV IV II II II III IV IV 
YearWater quality grade
#1
#2
#3
#4
#5
WNNNMRBPWNNNMRBPWNNNMRBPWNNNMRBPWNNNMRBP
2004 IV IV III II III IV III II III III 
2005 IV IV IV II II IV IV III II III IV III II 
2006 IV IV IV IV III IV IV II 
2007 IV IV III II IV IV II III III II 
2008 IV IV III III IV IV IV IV II IV 
2009 IV IV III II IV IV IV IV III 
2010 IV IV III II IV III II II II II II IV 
2011 IV IV II III IV IV II II II III IV IV 

NMR, The INPI method.

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