摘要
用神经网络和遗传算法(BP-GA)优化电沉积Cu-W的工艺参数。结果显示:BP-GA预测结果与试验结果较接近,相对误差为9.05%,说明BP-GA优化电沉积工艺参数有较高的预测能力和准确度。
The process parameters of Cu-W electrodeposition were optimized based on BP neural network and genetic algorithm. Results showed that prediction result was approach to experimental result,and the relative error was 9.05%,which indicating that BP neural network and genetic algorithm have high forecasting accuracy and was suitable for electrodeposition parameters prediction.
出处
《电镀与环保》
CAS
CSCD
北大核心
2015年第2期12-13,共2页
Electroplating & Pollution Control
基金
国家自然科学基金(No.50964008)
贵州省科学技术基金黔科合J字[2012]2114号
关键词
BP-GA
电沉积
Cu-W
工艺参数
BP neural network and genetic algorithm
electrodeposition
Cu-W
process parameters
