Modeling the Effects of Cu Content and Deformation Variables on the High-Temperature Flow Behavior of Dilute Al-Fe-Si Alloys Using an Artificial Neural Network

Hot deformation behavior and rate-controlling mechanism in dilute Al–Fe–Si alloys with minor additions of Mn and Cu

(2015) M. Shakiba et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation

(2015) Tzu-Tsung Wong   PATTERN RECOGNITION

Effect of Iron and Silicon Content on the Hot Compressive Deformation Behavior of Dilute Al-Fe-Si Alloys

(2014) M. Shakiba et al.   JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE

Effect of homogenization treatment and silicon content on the microstructure and hot workability of dilute Al–Fe–Si alloys

(2014) M. Shakiba et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Artificial neural network modeling to predict the hot deformation behavior of an A356 aluminum alloy

(2013) N. Haghdadi et al.   MATERIALS & DESIGN

Constitutive equations for elevated temperature flow behavior of commercial purity aluminum

(2012) H.R. Rezaei Ashtiani et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Comparison of the influence of Si and Fe in 99.999% purity aluminum and in commercial-purity aluminum

(2012) Qinglong Zhao et al.   SCRIPTA MATERIALIA

A hybrid approach for processing parameters optimization of Ti-22Al-25Nb alloy during hot deformation using artificial neural network and genetic algorithm

(2011) Yu Sun et al.   INTERMETALLICS

A phenomenological constitutive model for high temperature flow stress prediction of Al–Cu–Mg alloy

(2011) Y.C. Lin et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Artificial neural network prediction to the hot compressive deformation behavior of Al–Cu–Mg–Ag heat-resistant aluminum alloy

(2011) Zhilun Lu et al.   MECHANICS RESEARCH COMMUNICATIONS

Flow curve prediction of Al–Mg alloys under warm forming conditions at various strain rates by ANN

(2010) Serkan Toros et al.   APPLIED SOFT COMPUTING

Development of constitutive relationship model of Ti600 alloy using artificial neural network

(2010) Y. Sun et al.   COMPUTATIONAL MATERIALS SCIENCE

A critical review of experimental results and constitutive descriptions for metals and alloys in hot working

(2010) Y.C. Lin et al.   MATERIALS & DESIGN

Artificial Neural Network Modeling to Evaluate and Predict the Deformation Behavior of ZK60 Magnesium Alloy During Hot Compression

(2010) Y. J. Qin et al.   MATERIALS AND MANUFACTURING PROCESSES

High temperature deformation behavior of Al–Cu–Mg alloys micro-alloyed with Sn

(2010) Sanjib Banerjee et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Constitutive model for high temperature deformation of titanium alloys using internal state variables

(2009) Jiao Luo et al.   MECHANICS OF MATERIALS

Artificial neural network modeling to evaluate and predict the deformation behavior of stainless steel type AISI 304L during hot torsion

(2008) Sumantra Mandal et al.   APPLIED SOFT COMPUTING

A physically based constitutive model for fcc metals with applications to dynamic hardness

(2008) George Z. Voyiadjis et al.   MECHANICS OF MATERIALS