Hot deformation behavior and artificial neural network modeling of β-γ TiAl alloy containing high content of Nb

Hot Deformation ◽

Deformation Behavior ◽

Tial Alloy ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling to Predict Hot Deformation Behavior of Zn-Al Alloy

TMS 2016 145th Annual Meeting & Exhibition ◽

10.1007/978-3-319-48254-5_50 ◽

2016 ◽

pp. 417-424

Author(s):

Yingli Liu ◽

Jiancheng Yin ◽

Ying Jiang ◽

Yi Zhong

Keyword(s):

Neural Network ◽

Hot Deformation ◽

Deformation Behavior ◽

Network Modeling ◽

Neural Network Modeling ◽

Al Alloy ◽

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

Materials and Manufacturing Processes ◽

10.1080/10426910903124894 ◽

2010 ◽

Vol 25 (7) ◽

pp. 539-545 ◽

Cited By ~ 32

Author(s):

Y. J. Qin ◽

Q. L. Pan ◽

Y. B. He ◽

W. B. Li ◽

X. Y. Liu ◽

...

Keyword(s):

Neural Network ◽

Magnesium Alloy ◽

Deformation Behavior ◽

Network Modeling ◽

Hot Compression ◽

Neural Network Modeling ◽

Artificial Neural ◽

Zk60 Magnesium Alloy

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

Materials & Design (1980-2015) ◽

10.1016/j.matdes.2012.12.082 ◽

2013 ◽

Vol 49 ◽

pp. 386-391 ◽

Cited By ~ 102

Author(s):

N. Haghdadi ◽

A. Zarei-Hanzaki ◽

A.R. Khalesian ◽

H.R. Abedi

Keyword(s):

Neural Network ◽

Aluminum Alloy ◽

Deformation Behavior ◽

Network Modeling ◽

Neural Network Modeling ◽

A356 Aluminum Alloy ◽

A356 Aluminum

Role of Grain Size and Oxide Dispersion Nanoparticles on the Hot Deformation Behavior of AA6063: Experimental and Artificial Neural Network Modeling Investigations

Metals and Materials International ◽

10.1007/s12540-020-00950-z ◽

2021 ◽

Author(s):

A. Asgharzadeh ◽

H. Asgharzadeh ◽

A. Simchi

Keyword(s):

Neural Network ◽

Grain Size ◽

Deformation Behavior ◽

Network Modeling ◽

Neural Network Modeling ◽

Oxide Dispersion ◽

Artificial Neural Network Modeling

Artificial Neural Network Modeling of Pavement Performance using Expert Judgement

Road Materials and Pavement Design ◽

10.3166/rmpd.3.373-384 ◽

2002 ◽

Vol 3 (4) ◽

pp. 373-384

Author(s):

Medhi Parvani

Keyword(s):

Neural Network ◽

Network Modeling ◽

Pavement Performance ◽

Expert Judgement ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling of Phytoestrogen Binding to Estrogen Receptors

Letters in Drug Design & Discovery ◽

10.2174/157018006778194871 ◽

2006 ◽

Vol 3 (7) ◽

pp. 436-442 ◽

Cited By ~ 4

Author(s):

S. Agatonovic-Kustrin ◽

J. Turner

Keyword(s):

Neural Network ◽

Estrogen Receptors ◽

Network Modeling ◽

Neural Network Modeling ◽

Innovations in Corrosion and Materials Science (Formerly Recent Patents on Corrosion Science) ◽

An Artificial Neural Network Modeling to Study Unpredictable Degradation of Carbon Steel Marine Structure with Environmental Variables: Chloride, Sulphate, Bicarbonates, pH

10.2174/2352094904999141202103233 ◽

2015 ◽

Vol 4 (2) ◽

pp. 127-133

Author(s):

Subir Paul ◽

Sujit K Guchhait ◽

Kamal Goswami

Keyword(s):

Neural Network ◽

Carbon Steel ◽

Environmental Variables ◽

Network Modeling ◽

Neural Network Modeling ◽

Marine Structure ◽

Porosity Estimation of Mesoporous TiO 2 ‐ZnO Nanocrystalline by Artificial Neural Network Modeling

Chemical Engineering & Technology ◽

10.1002/ceat.202000297 ◽

2021 ◽

Author(s):

Soroush Soltani ◽

Taha Roodbar Shojaei ◽

Nasrin Khanian ◽

Thomas Shean Yaw Choong ◽

Nilofar Asim ◽

...

Keyword(s):

Neural Network ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural ◽

Porosity Estimation

Numerical and artificial neural network modeling study on the first-law and second-law performance of a novel helical heat sink filled with water–silver nanofluid

Journal of Thermal Analysis and Calorimetry ◽

10.1007/s10973-021-10697-3 ◽

2021 ◽

Author(s):

Mohammad Reza Salehfekr Arabani ◽

Nader Pourmahmoud ◽

Iraj Mirzaii

Keyword(s):

Neural Network ◽

Heat Sink ◽

Network Modeling ◽

Neural Network Modeling ◽

Second Law ◽

Artificial Neural ◽

Modeling Study

Analysis of diclofenac removal by metal-organic framework MIL-100(Fe) using multi-parameter experiments and artificial neural network modeling

Journal of the Taiwan Institute of Chemical Engineers ◽

10.1016/j.jtice.2021.04.021 ◽

2021 ◽

Author(s):

Ho-Young Jang ◽

Jin-Kyu Kang ◽

Seung-Chan Lee ◽

Jeong-Ann Park ◽

Song-Bae Kim

Keyword(s):

Neural Network ◽

Metal Organic Framework ◽

Network Modeling ◽

Neural Network Modeling ◽

Metal Organic ◽

Artificial Neural ◽

Organic Framework