摘要
本文用神经网络BP优化电镀Cu-W-Ni工艺。BP预测数据与同参数正交实验结果相同,优化后的CuW-Ni镀层质量好。说明BP神经网络有很好的非线性映射能力和泛化能力,与传统的实验方法比较,优化复杂的电镀工艺参数更具有优越性。
Back- propagation neural network （BP）is used to optimize electrodepositing parameters of Cu -W - Ni alloy coatings in this paper. Predication result in BP is similar to orthogonal test with the same parameters. In other words, BPhas better nonlinear mapping capability and generalization ability, which is superior to optimize electrodepositing technology parameters compared to traditional experimental methods.
出处
《现代机械》
2014年第3期31-33,共3页
Modern Machinery
基金
贵州省科学技术基金黔科合J字[2012]2114号
关键词
BP电镀
Cu—W—Ni
正交试验
工艺
back - propagation neural network
electro deposition
Cu - W - Ni alloy coatings
orthogonal test
technology parameters
