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Table 1 The generalized linear model and generalized additive model constructed by training data

From: A combined approach of generalized additive model and bootstrap with small sample sets for fault diagnosis in fermentation process of glutamate

 

Generalized linear model

Generalized additive model

Estimates for parametric functions

 Intercept

1466* (573)

47.35*** (0.22)

 T

2.64*** (0.19)

–

 DO

0.02 (0.08)

–

 OUR

−0.01 (0.07)

–

 CER

−0.06* (0.09)

–

 SS

0.01 (0.02)

 

 pH

−3.01 (23.69)

–

 Temp

−45.16* (17.70)

 

Degrees of freedom for smooth terms

 s(T)

–

7.96***

 s(DO)

–

2.34**

 s(OUR)

–

3.00**

 s(CER)

–

3.71***

 Adjusted R 2

0.940

0.996

 GCV score

44

4

  1. Data in parentheses represent standard errors of the parametric functions
  2. T fermentation time, DO dissolved oxygen, OUR oxygen uptake rate, CER carbon dioxide evolution rate, SS stirring speed, Temp temperature, GCV generalized cross-validation
  3. * P < 0.05
  4. ** P < 0.01
  5. *** P < 0.001