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

Journal of Applied Sciences ›› 1994, Vol. 12 ›› Issue (3): 253-258.

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

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

Shanghai institure of Metallurgy, Academia Sinica

Received:1991-04-13 Revised:1992-05-06 Online:1994-09-30 Published:1994-09-30

Abstract

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-T_c 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

CAI YUDONG, LIU HONGLIN, GAN JUNREN, YAO LINSHEN, CHEN NIANYI. B-P LEARNING ALGORITHM OF NEURAL NETWORK AND ITS APPLICATION TO THE SYNTHESIS OF HIGH-T_c SUPERCONDUCTOR Bi-BASED DOPED F[J]. Journal of Applied Sciences, 1994, 12(3): 253-258.

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

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

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