Table 16 Comparison of prediction capability of various models and developed ANFIS-NSGA-II.

From: Modelling of compression ignition engine by soft computing techniques (ANFIS-NSGA-II and RSM) to enhance the performance characteristics for leachate blends with nano-additives

References

Model

Fuel

RMSE

R2

Seraj et al.24

ANFIS-GA

Eucalyptus

3.470

0.38

Khan42

ANFIS

Eichhornia Crassipes

6.426

0.24

Aghbashlo et al.43

ANFIS-ALFIMO

Waste cooking oil

0.423

0.92

BTE (current study) (ABD)

ANFIS-NSGA-II

Waste food oil

0.210

0.99

BSEC (current study) (ABD)

ANFIS-NSGA-II

Waste food oil

0.272

0.93

NOx (current study) (ABD)

ANFIS-NSGA-II

Waste food oil

0.698

0.90

CO (current study) (ABD)

ANFIS-NSGA-II

Waste food oil

0.470

0.93

UBHC (current study) (ABD)

ANFIS-NSGA-II

Waste food oil

0.415

0.94

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