2019
DOI: 10.1039/c9ra04927d
|View full text |Cite
|
Sign up to set email alerts
|

Application of ANN modeling techniques in the prediction of the diameter of PCL/gelatin nanofibers in environmental and medical studies

Abstract: Prediction of the diameter of a nanofiber is very difficult, owing to complexity of the interactions of the parameters which have an impact on the diameter and the fact that there is no comprehensive method to predict the diameter of a nanofiber. Therefore, the aim of this study was to compare the multi-layer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) models to develop mathematical models for the diameter prediction of poly(3-caprolactone) (PCL)/gelatin (Gt) nanofibers.Four… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
34
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
8

Relationship

5
3

Authors

Journals

citations
Cited by 59 publications
(35 citation statements)
references
References 58 publications
1
34
0
Order By: Relevance
“…In general, decreasing fiber size is due to the fact that the surface of charge on the jet at higher voltage or field increased. This observation is similar to the previously published reports 21,48,49 . Figure 6(c) provides the effect of the injection rate on the diameter of nanofibers.…”
Section: Discussionsupporting
confidence: 93%
See 1 more Smart Citation
“…In general, decreasing fiber size is due to the fact that the surface of charge on the jet at higher voltage or field increased. This observation is similar to the previously published reports 21,48,49 . Figure 6(c) provides the effect of the injection rate on the diameter of nanofibers.…”
Section: Discussionsupporting
confidence: 93%
“…The accuracy of multilayer perceptron artificial neural network (MLP) in comparison with other ANN techniques such as Radial Basis Function (RBF) and Support Vector Machine (SVM) in nanofibers diameter prediction has been proved in recent researches. Researchers declared that the reliable results of the ANN in nanofiber studies are in the complex interactions between the variables which are influencing nanofiber formation 21 . However, the capability of ANN techniques, in nanofibers diameter prediction, has not been compared with classic regression methods such as MLR.…”
mentioning
confidence: 99%
“…Considering two classes of trees failure (0 and 1) in this research, we have two output layers in the structure of RBFNN. Gaussian function is the most frequently used function in the hidden layers of RBFNN 13 , 27 . The Gaussian function can find the center of circular classifiers successfully.…”
Section: Methodsmentioning
confidence: 99%
“…Model accuracy was estimated based on the following indices: coefficient of determination (R 2 ), mean absolute error (MAE), and mean square error (MSE) (Eqs. 5 to 7 [ 50 52 ]). …”
Section: Methodsmentioning
confidence: 99%
“…Model accuracy was estimated based on the following indices: coefficient of determination (R 2 ), mean absolute error (MAE), and mean square error (MSE) (Eqs. 5 to 7 [50][51][52]). In these equations: O i : measured data, P i : predicted data, O ave : mean measured data, P ave : the average of predicted data and n: number of the samples.…”
Section: Modeling S Limbata Seed Germinationmentioning
confidence: 99%