A one-by-one learning algorithm for multi-layer neural network modelling is presented based on the back-propagation mechanism of network error.
基于误差反向传播的机制，针对连续制造过程的预测与控制，提出多层神经网络的逐个样本学习算法。
Study modelling thought, network configuration, majorize GNNM(1,1) mode method and learning algorithm of GNNM(1,1) mode combined grey system theory and neural network.
研究了灰色系统理论与神经网络组合的灰色神经网络GNNM（1，1）模型的建模思想、网络结构及其优化GNNM（1，1）模型的方法和学习算法；
Multilayered neural network offers a new exciting alternative for modelling unknown nonlinear dynamical system.
神经网络为未知非线性动态系统的建模提供了一条新途径。
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