Table 4 Detail of ACOFIS and ANFIS setup and learning times.

From: Pressure and temperature predictions of Al2O3/water nanofluid flow in a porous pipe for different nanoparticles volume fractions: combination of CFD and ACOFIS

Method

ACOFIS method

ANFIS method

Number of inputs

3

3

Percentage of data in training process

77

77

Number of iterations

115

115

Clustering Type

Fuzzy C-mean Clustering

Fuzzy C-mean Clustering

Exponent as FCM clustering parameter

2

2

Minimum Improvement as FCM clustering parameter

1.00E-05

1.00E-05

Correlation coefficient (R) in training process

0.997867326

0.99999993

Coefficient of determination (R2) in training process

0.995739201

0.99999986

RMSE error in testing process

1.331970484

0.025145357

Correlation coefficient (R) in testing process

0.997857536

0.999998829

Coefficient of determination (R2) in testing process

0.995719663

0.999997657

Learning process time (s)

198.0029725

212.5959348

Prediction process time (s)

0.1300083

0.519412

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