English

应用科学学报 ›› 1994, Vol. 12 ›› Issue (3): 253-258.

• 论文 • 上一篇    下一篇

神经网络B-P学习算法及其在含F铋系高温超导体制备中的应用

蔡煜东, 刘洪霖, 甘俊人, 姚林声, 陈念贻   

  1. 中国科学院上海冶金研究所
  • 收稿日期:1991-04-13 修回日期:1992-05-06 出版日期:1994-09-30 发布日期:1994-09-30

B-P LEARNING ALGORITHM OF NEURAL NETWORK AND ITS APPLICATION TO THE SYNTHESIS OF HIGH-Tc SUPERCONDUCTOR Bi-BASED DOPED F

CAI YUDONG, LIU HONGLIN, GAN JUNREN, YAO LINSHEN, CHEN NIANYI   

  1. Shanghai institure of Metallurgy, Academia Sinica
  • Received:1991-04-13 Revised:1992-05-06 Online:1994-09-30 Published:1994-09-30

PDF

72

被引次数

2

摘要： 叙述"反向传播"神经网络的结构、算法及其在含F铋系高温超导体制备中的应用.实验结果表明神经网络的判别正确率为100%.因此,该方法可用于材料设计等高层次知识处理领域.

关键词: 神经网络, 材料设计, 模式识别

Abstract: Great attention is now being paid to neural network in pattern recognition and other fields. The structure of neural network,the back propagation algorithm for neural network and its application to the synthesis of high-Tc superconductorBi-based doped F are presented in this paper.The experimental results show that the performance of the neural network model is good,and therefore the model may be used in material design and other fields.

Key words: pettern recognition, neural network, material design