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Volumn 9, Issue 2, 2012, Pages 119-124

Modeling of mechanical properties of as-cast Mg-Li-Al alloys based on PSO-BP algorithm

Author keywords

Artificial neural networks; BP algorithm; Mechanical; Mg Li Al alloys; Particle swarm optimization

Indexed keywords


EID: 84862679968     PISSN: 16726421     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (8)

References (14)
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    • Huashun, Y.1    Min, G.2    Chen, X.3
  • 2
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    • Effects of Ca on the Microstructures and Mechanical Properties of Mg-Li-Al Alloys
    • (in Chinese)
    • Li Hongbin, Yao Guangchun, Ji Haibin, Liu Yihan, Guo Zhiqiang. Effects of Ca on the Microstructures and Mechanical Properties of Mg-Li-Al Alloys. Foundry, 2005, 54(12), 1276-1279. (in Chinese)
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  • 3
    • 34249723766 scopus 로고    scopus 로고
    • The use of artificial neural network in materials science based research
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    • (2007) Materials and Design , vol.28 , pp. 1747-1752
    • Sha, W.1    Edwards, K.L.2
  • 4
    • 57149118632 scopus 로고    scopus 로고
    • Artificial neural network approach to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys
    • Mehmet S O and Sedat K. Artificial neural network approach to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys. Materials and Design, 2009, 30: 764-769.
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  • 5
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    • Predicting properties for secondary aging of 7055 Al alloy based on artificial neural networks
    • (in Chinese)
    • Zhou Guwei, Zheng Ziqiao, Li Hai. Predicting properties for secondary aging of 7055 Al alloy based on artificial neural networks. The Chinese Journal of Nonferrous Metals, 2006, 16(9):1583-1588. (in Chinese)
    • (2006) The Chinese Journal of Nonferrous Metals , vol.16 , Issue.9 , pp. 1583-1588
    • Guwei, Z.1    Ziqiao, Z.2    Li, H.3
  • 6
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    • Modeling the correlation between processing parameters and properties in titanium alloys using artificial neural network
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    • (2001) Computational Materials Science , vol.21 , pp. 375-394
    • Malinov, S.1    Sha, W.2    McKeown, J.J.3
  • 7
    • 77950605191 scopus 로고    scopus 로고
    • Aluminum-zinc alloy squeeze casting technological parameters optimization based on PSO and ANN
    • Shu Fuhua. Aluminum-zinc alloy squeeze casting technological parameters optimization based on PSO and ANN. China Foundry, 2007, 4(3): 202-205.
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  • 8
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    • An artificial neural network model for the prediction of ageing properties of ultra high strength Al-Zn-Mg-Cu-Zr-Ag alloy
    • (in Chinese)
    • Zeng Yu, Zhu Yuanzhi, Yin Zhimin. An artificial neural network model for the prediction of ageing properties of ultra high strength Al-Zn-Mg-Cu-Zr-Ag alloy. Rare Metal Materials and Engineering, 2005, 34(5):726-730. (in Chinese)
    • (2005) Rare Metal Materials and Engineering , vol.34 , Issue.5 , pp. 726-730
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  • 9
    • 84855264438 scopus 로고    scopus 로고
    • Model of constitutive relationship for 2D70 aluminum alloy based on BP neural network
    • (in Chinese)
    • Lu Shiqiang, Zhou Xilin, Wang Kelu, Li Xin, Zhao Weigang. Model of constitutive relationship for 2D70 aluminum alloy based on BP neural network. Forging & Stamping Technology, 2008, 33(1):148-151. (in Chinese)
    • (2008) Forging & Stamping Technology , vol.33 , Issue.1 , pp. 148-151
    • Shiqiang, L.1    Xilin, Z.2    Kelu, W.3    Li, X.4    Weigang, Z.5
  • 10
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    • Xi'an, China: XiDian University of Science and Technology Press, (in Chinese)
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.