[1] [1] Zuo Tiechuan. Laser Materials Processing of High Strength Aluminum Alloy [M]. Beijing: National Defence Industry Press, 2002

[2] [2] Huang Kaijin, Lin Xin, Chen Chi et al.. Microstructure and wear behaviour of laser-clad Zr-Cu-Ni-Al/ TiC composites on AZ91D magnesium alloy [J]. Chinese J. Lasers, 2007, 34(4):449～554

[3] [3] Liu Hongbin, Wang Cunshan, Gao Yali et al.. Laser cladding amorphous composite coating of Cu-Zr-Al on magnesium alloy surface [J]. Chinese J. Lasers, 2006, 33(5):709～713

[4] [4] Niu Xin, Chao Mingju, Wang Wenli et al.. In situ synthesized NbC particulate reinforced Ni-based composite coatings by laser cladding [J]. Chinese J. Lasers, 2006, 33(7):987～992

[5] [5] Liu Rongxiang, Ji Zesheng. Microscopic morphology and microstructure of phases between dilution zone and clad zone in laser remelting NiCrBSi/ TiN layer [J]. Chinese J. Lasers, 2007, 34(9):1292～1296

[6] [6] E. Toyserkani, A. Khajepour, S. Corbin. Laser Cladding [M]. Boca Raton, London, New York, Washington, D.C.: CRC press, 2005

[7] [7] Li Jingxian, Yan Cheng, Wu Jiqiu. Prospect of ANN in materials science and engineering[J]. China Ceramic Industry, 2003, 10(4):36～38

[8] [8] Ding Zhouhua, Zheng Qiguang, Tong Xinglin et al.. Optimizing of laser cladding parameters of Co-based hard alloy coating based on artificial neural networks [J]. J. Optoelectronics·Laser, 2004, 15(3):353～355

[9] [9] Wang Dacheng. Controlling laser surface strengthening artificial neural network [J]. Laser Technology, 2003, 27(4):317～320

[10] [10] Xu Dapeng, Zhou Jianzhong, Guo Huafeng. Application for laser cladding forming using evolutionary neural networks [J]. Applied Laser, 2006, 26(5):303～306

[11] [11] Theory of Neural Network and Realization of MATLAB 7 [M]. Beijing: Publishing House of Electronics Industry, 2006. 99～108