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神經網絡在梯度功能材料制備中的應用

Application of Neural Network to the Process of Functionally Gradient Materials Fabrication

  • 摘要: 針對梯度功能材料(FGM)制備過程的復雜性,提出了利用神經網絡信息處理機制進行制備材料的特性預估;實例分析表明,這一方法是有效的.同時,針對BP學習算法速度較慢,易陷入局部極小的缺點,改用函數型連接網絡來提高學習速度.試驗表明學習速度提高顯著.

     

    Abstract: Taking account of complecities of the Functionally Gradient Materials (FGM) fabrication process, a neural network based expert system which estimates the properities of the material is presented. The experimental results show that this method is effective. To improve the learning speed of the system and reduce the possibility of local minimum, a functional-linked net is introduced. The application indicates that both learning speed and accuracy of the estimation are satisfactory.

     

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