摘要
本文将前向人工神经网络技术用于酸洗工艺设计过程，建立了钎焊材料的酸洗工艺设计模型，实验证明该模型能准确预测ＣｕＺｎＡｇ钎焊材料的酸洗效益、能有效设计不同前期生产条件下的酸洗工艺。
In this paper,the self-learning ability and the classification function of the artificial neural network(ANN)were used to study the acid treatment process of solder alloys.Based on the experimental data obtained in the factory,an ANN was established. The trained ANN could acquire the relations between the production conditions and acid treatment effects, From the verification of CuZnAg solder,it is proved that the neural network could successfully predict the effects of the acid treatment,and could easily determine the parameters of the acid treatment process(acid concentration and acid treatment time)under different production conditions.It is concluded that the ANN provides an effective method for predicting the properties of materials.It is also a basis for further materials design.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
1995年第2期1-5,共5页
Journal of Tsinghua University(Science and Technology)
基金
国家863高技术资助
关键词
神经网络
钎焊材料
酸处理
酸洗工艺
artificial neural networks
CuZnAg solder
acid treatment
property prediction
materials design
