Comparison of Linear Multivariable, Partial Least Square Regression, and Artificial Neural Network Analyses to Study the Effect of Different Parameters on Anode Properties-Reference-Cited by-同舟云学术

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Comparison of Linear Multivariable, Partial Least Square Regression, and Artificial Neural Network Analyses to Study the Effect of Different Parameters on Anode Properties

Published:2015-02-20 Issue: Volume: Page:1129-1134
ISSN:
Container-title:Light Metals 2015
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Author:

Bhattacharyay Dipankar,Kocaefe Duygu,Kocaefe Yasar,Morais Brigitte

Publisher

John Wiley & Sons, Inc.

Reference26 articles.

1. D. Kocaefe A. Sarkar S. Das S. Amrani D. Bhattacharyay D. Sarkar Y. Kocaefe B. Morais M. Gagnon Review of different techniques to study the interactions between coke and pitch in anode manufacturing TMS Light Metals, Texas, USA, 2013

2. S. Schlotzhauer Elementary statistics using JMP SAS Press, Cary, NC: SAS Institute, 2007 166 169

3. D. L. Rubinfeld Reference Manual on Scientific Evidence Third Edition, The national academies press, Washington, 2011 179 227

4. R. J. Stonier X. H. Yu Complex Systems: Mechanism of Adaptation IOS press, Washington, 1994 257 259

5. Comparison of growth models between artificial neural networks and nonlinear regression analysis in Cherry Valley ducks;Kaewtapee;Applied Poultry Research,2011

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An artificial neural network model for predicting the CO2 reactivity of carbon anodes used in the primary aluminum production;Neural Computing and Applications;2015-11-14

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