Estimation of diameters of PVP nanofibers with artificial neural networks algorithms

Nanofibers are manufactured with Polyvinylpyrrolidone (PVP) polymer,water and alcohol solution and using electrospinning process in this research,data set is created with using flow rate for nanofibers which are manufactured,with using needle point,distance between plate and using applied voltage value.Analysis of nanofibers is determined with scanning electron microscope,diameter is determined with Fibraquant schedule.It takes a long time to make traditional test process in laboratory and also their cost is really too high. Estimation and anaylsis for future are estimated with obtained values which are result of remark in past and help of created models.Artificial neural networks and deep learning algorithms are process which are fairly used in estimation space nowadays.In this study,artificial neural networks and deep learning algorithms are used for guessing diameter of nanofibers. With Artificial Neural Networks and Deep Learning algorithms, 4 independent variables affecting the diameter of nanofibers were determined as input variables and nanofiber diameter values were determined as output variables, and the results obtained from these models were compared with the literature. Study shows that artificial neural networks and deep learning algorithms can be practised at applications for measuring diameters of nanofibers.Because of small amount for data,it is determeined that model for artificial neural network is more successful than deep learning model.