کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9796613 | 1514950 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of grain size of Al-7Si Alloy by neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
دانش مواد (عمومی)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Neural networks, which are known for mapping non-linear and complex systems, have been used in the present study to model the grain-refinement behavior of Al-7Si alloy. The development of a feed forward neural network (FFNN) model with back-propagation (BP) learning algorithm has been presented for the prediction of the grain size, as a function of Ti and B addition level and holding time during grain refinement of Al-7Si alloy. Comparison of the predicted and experimental results shows that the FFNN model can predict the grain size of Al-7Si alloy with good learning precision and generalization.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials Science and Engineering: A - Volume 391, Issues 1â2, 25 January 2005, Pages 131-140
Journal: Materials Science and Engineering: A - Volume 391, Issues 1â2, 25 January 2005, Pages 131-140
نویسندگان
N.S. Reddy, A.K. Prasada Rao, M. Chakraborty, B.S. Murty,