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Table 2 Summary of results of selected models by BMA method

From: Application of artificial intelligence for forecasting surface quality index of irrigation systems in the Red River Delta, Vietnam

 

p! = 0

EV

SD

Model 1

Model 2

Model 3

Model 4

Model 5

Intercept

100.0

3.317e+01

1.404e+01

4.104e+01

3.783e+01

3.906e+01

8.806e+00

1.066e+01

BOD5

92.1

− 5.236e−01

1.822e−01

− 5.718e−01

− 5.954e−01

− 5.784e−01

− 5.986e−01

− 5.823e−01

COD

15.2

− 2.276e−02

6.155e−02

     

NH4

100.0

− 1.403e+00

2.596e−01

− 1.404e+00

− 1.411e+00

− 1.400e+00

− 1.368e+00

− 1.358e+00

PO4

92.5

− 6.661e+00

2.828e+00

− 7.106e+00

− 7.320e+00

− 7.047e+00

− 7.557e+00

7.288e+00

NTU

71.9

− 1.625e−01

1.212e−01

− 1.872e−01

− 2.603e−01

 

− 2.535e−01

 

TSS

62.8

− 1.255e−01

1.123e−01

− 1.712e−01

 

− 2.385e−01

 

− 2.309e−01

Coliform

96.6

− 7.360e−06

2.597e−06

− 7.576e−06

− 7.522e−06

− 7.994e−06

− 7.565e−06

− 8.025e−06

DO

100.0

4.149e+00

4.468e−01

4.101e+00

4.141e+00

4.092e+00

4.054e+00

4.009e+00

Temp

0.0

0.000e+00

0.000e+00

     

pH

19.3

7.896e−01

1.841e+00

   

3.973e+00

3.877e+00

nVar

   

7

6

6

7

7

r2

   

0.387

0.381

0.381

0.384

0.384

BIC

   

− 3.34e+02

− 3.34e+02

− 3.34e+02

− 3.31e+02

− 3.31e+02

post prob

   

0.209

0.193

0.190

0.054

0.047