摘要
以BP反传理论为基础，建立了对Osprey过程的前向多层神经网络，并对其进行测试．利用这一方法研究了Osprey过程中部分参数对孔隙度的影响．结果证明该网络较好地实现了学习和预测．
Artificial neural networks for the Osprey process based on back-propagationare established and some tests are conducted. The relationship between the processingparameters and the outputs are simulated with the networks. It is shown that neuralnetworks are successfully used to pridict porosity values of the process.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
1997年第1期59-62,共4页
Journal of University of Science and Technology Beijing
基金
国家自然科学基金
