Biomedical Prediction of Radial Size of Powdered Element using Artificial Neural Network
Yaagyanika Gehlot1, Bhairvi Sharma1, P. Muthu1, Hariharan Muthusamy1 and S. Latha21Department of Biomedical Engineering SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India.
2Department of Electronics and Communication Engineering SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India.
Corresponding Author E-mail: muthu.p@ktr.srmuniv.ac.in
Abstract: Silver nitrous aqueous solution is used to biosynthesize Silver nanoparticles (Ag-NPs) through a green and easy way using tuber powder extracts of Curcuma Longa (C. longa). The aim is to model an Artificial Neural Network (ANN) using seven existing algorithms in MATLAB for forecasting the size of the silver nanoparticle with volume of both C. longa extraction and AgNO3, time of stirring and temperature of reaction as input functions. Several techniques including Quasi-Newton, Conjugate Gradient and Levenberg-Maquardt are employed for training the designed ANN model, a feed-forward backpropagation network with different combinations of architecture and transfer functions. Each algorithm is fashioned to obtain the best performance by calculating the Regression (R), Mean Square Error (MSE), Mean Absolute Error (MAE) and Error Sum of Squares (SSE), thereby comparing the results and propounding the optimum algorithm technique for the discussed application in nanoengineering. Finally, based on the findings, the optimum network is proposed through the simulation results.
Keywords: Artificial Neural Network; Feed-forward Back Propagationl Learning Algorithms; Nanoengineering, Silver Nanoparticles Back to TOC