APPLIED LASER, Volume. 42, Issue 10, 41(2022)
Prediction on Geometrical Characteristics and Properties of Cladding Layer Based on BP Network Improved by Different Algorithms
[1] [1] GOODARZI D M, PEKKARINEN J, SALMINEN A. Analysis of laser cladding process parameter influence on the clad bead geometry[J]. Welding in the World, 2017, 61(5): 883-891.
[17] [17] BRINKSMEIER E, MEYER D, HUESMANN-CORDES A G, et al. Metalworking fluids-Mechanisms and performance[J]. CIRP Annals, 2015, 64(2): 605-628.
[20] [20] HOLLAND J H. Genetic algorithms[J]. Scientific American, 1992, 267(1): 66-72.
[22] [22] WANG Y, ZHOU Q Y, LI K, et al. Preparation of Ni-W-SiO2 nanocomposite coating and evaluation of its hardness and corrosion resistance[J]. Ceramics International, 2015, 41(1): 79-84.
[23] [23] ZHOU J L, DUAN Z C, LI Y, et al. PSO-based neural network optimization and its utilization in a boring machine[J]. Journal of Materials Processing Technology, 2006, 178(1-3): 19-23.
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Wu Jialing, Qi Wenjun, Wang Xuxiang, Zhang Shuang, Zhang Rong. Prediction on Geometrical Characteristics and Properties of Cladding Layer Based on BP Network Improved by Different Algorithms[J]. APPLIED LASER, 2022, 42(10): 41
Received: Nov. 2, 2021
Accepted: --
Published Online: May. 23, 2024
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