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The Scientific World Journal
Volume 2014, Article ID 108492, 12 pages
http://dx.doi.org/10.1155/2014/108492
Research Article

A Comparative Study on Improved Arrhenius-Type and Artificial Neural Network Models to Predict High-Temperature Flow Behaviors in 20MnNiMo Alloy

School of Material Science and Engineering, Chongqing University, Chongqing 400044, China

Received 24 August 2013; Accepted 22 December 2013; Published 12 February 2014

Academic Editors: F. Berto and Y.-Y. Chen

Copyright © 2014 Guo-zheng Quan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [9 citations]

The following is the list of published articles that have cited the current article.

  • H. Elçiçek, E. Akdoğan, and S. Karagöz, “The Use of Artificial Neural Network for Prediction of Dissolution Kinetics,” The Scientific World Journal, vol. 2014, pp. 1–9, 2014. View at Publisher · View at Google Scholar
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  • Guo-zheng Quan, Shi-ao Pu, Zong-yang Zhan, Zhen-yu Zou, Ying-ying Liu, and Yu-feng Xia, “Modelling of the hot flow behaviors for Ti-13Nb-13Zr alloy by BP-ANN model and its application,” International Journal of Precision Engineering and Manufacturing, vol. 16, no. 10, pp. 2129–2137, 2015. View at Publisher · View at Google Scholar
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  • Guo-zheng Quan, Zhen-yu Zou, Hai-rong Wen, Shi-ao Pu, and Wen-quan Lv, “A Characterization of Hot Flow Behaviors Involving Different Softening Mechanisms by ANN for As-Forged Ti-10V-2Fe-3Al Alloy,” High Temperature Materials And Processes, vol. 34, no. 7, pp. 651–665, 2015. View at Publisher · View at Google Scholar
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  • Menghan Wang, Gentian Wang, Rui Wang, and Lie Meng, “Hot deformation and processing map of Mn-Ni-Mo system nuclear power steel,” Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology), vol. 48, no. 3, pp. 592–600, 2017. View at Publisher · View at Google Scholar
  • Guo-Zheng Quan, Tong Wang, Bo Liu, Zhen-Yu Zou, and Jun-Chao Li, “Modeling the Hot Deformation Behaviors of As-Extruded 7075 Aluminum Alloy by an Artificial Neural Network with Back-Propagation Algorithm,” High Temperature Materials and Processes, vol. 36, no. 1, pp. 1–13, 2017. View at Publisher · View at Google Scholar
  • Shin-Hyung Song, Yongbae Kim, and Seoung-Yong Lee, “Study on the High Temperature Deformation of Incoloy 825 Alloy using an Artificial Neural Network,” Journal of the Korean Society of Manufacturing Technology Engineers, vol. 27, no. 1, pp. 41–45, 2018. View at Publisher · View at Google Scholar