用前馈多层神经网络方法研究了高聚物的热力学性质。
The thermodynamical properties of polymers are studied using a BP artificial neural network model.
为了更好满足谐波测量的实时性和测量精度，我们进一步研究了基于多层前馈神经网络在谐波测量中的方法。
In order to improve the real-time and precision, the methods with multi-layer feed-forward neural networks are investigated more.
提出了一种利用多层前馈神经网络生成纹理图象的新方法。
In this paper, a new method to generate the texture image by use of Multi layer feed forward neural network is presented.
提出了径流长期分级预报的人工神经网络方法，给出了多层前馈网络的联合梯度算法。
An artificial neural network method is proposed for hydrological forecasting, the hybrid gradient method for multilayer feedforward neural network developed.
同时将所建立的模型与以往回归方法建模进行了比较，可以看出多层前馈神经网络要优于回归方法建立的模型。
At the same time, comparing the model with traditional model by regression method, we obtained that the former is better.
同时将所建立的模型与以往回归方法建模进行了比较，可以看出多层前馈神经网络要优于回归方法建立的模型。
At the same time, comparing the model with traditional model by regression method, we obtained that the former is better.
应用推荐