Artificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloys

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Date

2008

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

Citation