Artificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloys
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Date
2008
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science Sa
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
in this study, artificial neural network (ANN) approach was done to predict electrical conductivity and density of silver-nickel binary alloys using aback-propagation neural network that uses gradient descent learning algorithm. in ANN training module, Ag%. and Ni% (weight) contents were employed as input and electrical conductivity, calculated and typical density were used as outputs. ANN system was trained using the prepared training set (also known as learning set). After training process, the test data were used to check system accuracy. As a result the neural network was found successful for the prediction of electrical conductivity and density of silver nickel binary alloys. (C) 2008 Elsevier B.V. All rights reserved.
Description
Keywords
Artificial Neural Network, Electrical Conductivity, Density, Silver-Nickel Binary Alloys
Journal or Series
Journal of Materials Processing Technology
WoS Q Value
Q2
Scopus Q Value
Q1
Volume
208
Issue
1-3
