Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass
作者： Mohammad Hasan Shojaeefard , Mostafa Akbari , Mojtaba Tahani , Foad Farhani
DOI: 10.1155/2013/574914
关键词:
摘要: Al-Mg and CuZn34 alloys were lap joined using friction stir welding while the aluminum alloy sheet was placed on CuZn34. In addition, mechanical properties of each sample characterized shear tests. Scanning electron microscopy (SEM) X-ray diffraction analysis used to probe chemical compositions. An artificial neural network model developed simulate correlation between Friction Stir Lap Welding (FSLW) parameters properties. Subsequently, a sensitivity performed investigate effect input parameter output in terms magnitude direction. Four methods, namely, “PaD” method, “Weights” “Profile” “backward stepwise” which can give relative contribution and/or profile factors, compared. The PaD giving most complete results, found be useful, followed by Profile method that gave variables.
hindawi.com参考文章(16)
G. David Garson, Interpreting neural-network connection weights AI Expert archive. ,vol. 6, pp. 46- 51 ,(1991) , 10.5555/129449.129452
Yannis Dimopoulos, Paul Bourret, Sovan Lek, Use of some sensitivity criteria for choosing networks with good generalization ability Neural Processing Letters. ,vol. 2, pp. 1- 4 ,(1995) , 10.1007/BF02309007
Sarit Dutta, J.P. Gupta, PVT correlations for Indian crude using artificial neural networks Journal of Petroleum Science and Engineering. ,vol. 72, pp. 93- 109 ,(2010) , 10.1016/J.PETROL.2010.03.007
W. Wang, P. Jones, D. Partridge, Assessing the Impact of Input Features in a Feedforward Neural Network Neural Computing and Applications. ,vol. 9, pp. 101- 112 ,(2000) , 10.1007/PL00009895
Mohammad Hasan Shojaeefard, Reza Abdi Behnagh, Mostafa Akbari, Mohammad Kazem Besharati Givi, Foad Farhani, Modelling and Pareto optimization of mechanical properties of friction stir welded AA7075/AA5083 butt joints using neural network and particle swarm algorithm Materials & Design. ,vol. 44, pp. 190- 198 ,(2013) , 10.1016/J.MATDES.2012.07.025
Ming Lu, S. M. AbouRizk, U. H. Hermann, Sensitivity Analysis of Neural Networks in Spool Fabrication Productivity Studies Journal of Computing in Civil Engineering. ,vol. 15, pp. 299- 308 ,(2001) , 10.1061/(ASCE)0887-3801(2001)15:4(299)
Hasan Okuyucu, Adem Kurt, Erol Arcaklioglu, Artificial neural network application to the friction stir welding of aluminum plates Materials & Design. ,vol. 28, pp. 78- 84 ,(2007) , 10.1016/J.MATDES.2005.06.003
J. J. Monta�o, A. Palmer, Numeric sensitivity analysis applied to feedforward neural networks Neural Computing and Applications. ,vol. 12, pp. 119- 125 ,(2003) , 10.1007/S00521-003-0377-9
Mostafa Akbari, Reza Abdi Behnagh, Dissimilar Friction-Stir Lap Joining of 5083 Aluminum Alloy to CuZn34 Brass Metallurgical and Materials Transactions B-process Metallurgy and Materials Processing Science. ,vol. 43, pp. 1177- 1186 ,(2012) , 10.1007/S11663-012-9682-Y
A. Esmaeili, M.K. Besharati Givi, H.R. Zareie Rajani, A metallurgical and mechanical study on dissimilar Friction Stir welding of aluminum 1050 to brass (CuZn30) Materials Science and Engineering A-structural Materials Properties Microstructure and Processing. ,vol. 528, pp. 7093- 7102 ,(2011) , 10.1016/J.MSEA.2011.06.004