Deogratias Nurwaha and Xinhou
Abstract
This study presents the application of Artificial Intelligence (AI) techniques to predict the morphology of nanofibers produced by needless electrospinning method. Two straight and parallel copper wire electrodes electrospinning method was used to produce nanofibers. Using digital image processing software Image Journal, Mean Nanofiber Diameter (MFD) and Nanofiber Diameter Standard Deviation (NFSD) have been measured and recorded. Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Support Vector Machines (SVMs) and Gene Expression Programming (GEP) methods were used for prediction of electrospun nanofiber morphology. Prediction results and experimental were compared. It was found that SVMs model has better predictive power in comparison with both ANFIS and Gene Expression Programming models. However, results provided by both GEP and ANFIS are also acceptable. The relative importance of process parameters as contributor to the nanofiber morphology was also investigated. It was found that nanofiber morphology was strongly or weakly dependent on processing parameters.