对偶神经网络中激活函数对的改进

Compared with traditional method of numerical calculation, the dual neural network calculation method of multiple definite integral has the advantages of high efficiency and high precision, but in the process of actual traing, the precision and efficiency can not meet expectations. Hence, a great deal of studies focus on the construction of new activation functions of dual neural network, in this paper, we apply sigmoid/softplus as the new activation functions. The simulation by examples, compared with the dual neural network with traditional activation functions, the results show that the dual neural network with sigmoid/softplus activition functions has higher precision and can increase convergence speed.