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Future Journal of Pharmaceutical Sciences

Table 2 R2 and RMSE values of MNFF and MFFF using different training algorithms

From: Development of trigger sensitive hyaluronic acid/palm oil-based organogel for in vitro release of HIV/AIDS microbicides using artificial neural networks

Network architecture

Training algorithm

Response

Mucin adsorption

Flux

RMSE

R2

RMSE

R2

MNFF

IBP

7.34217

0.76591

0.19291

0.91433

BBP

15.81500

− 0.0859

0.21300

0.89556

QP

13.71700

0.18308

0.59388

0.18807

GA

7.57710

0.75073

0.22576

0.88267

LM

6.83070

0.79741

0.24737

0.85912

MFFF

IBP

6.56520

0.81286

0.12781

0.9624

BBP

16.91100

− 0.24175

0.69043

− 0.09741

QP

14.09100

0.13784

0.59431

0.18689

GA

7.92070

0.72760

0.29926

0.79383

LM

6.55470

0.81435

0.12148

0.96603

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