BP algorithm is the most popular training algorithm for feed forward neural network learning. But falling into local minimum and slow convergence are its drawbacks.
BP算法是前馈神经网络训练中应用最多的算法，但其具有收敛慢和陷入局部极值的严重缺点。
To improve the prediction results of protein secondary structure, we developed a neural network ensemble model based on dual-layer feed forward BP network.
为了提高蛋白质二级结构预测精度，本文尝试采用一种基于串联BP网络集成的二级结构预测模型。
The I/O relationship of back propagation algorithm (BP algorithm) for Feed-Forward Multi-layered Neural Network is a mapping relationship, which can resolve the above nonlinear problem.
多层前向神经网络的误差逆传播算法（简称BP算法）的输入输出关系实际上是一种映射关系，适于解决上述非线性映射问题。
The potential utility of feed forward artificial neural network using the back propagation algorithm (BP-ANN), in interpreting pyrogram data from traditional Chinese medicine was discussed.
将以误差反向传播为训练算法的前馈式人工神经网络（BP- ANN）首次用于中草药的裂解气相色谱谱图解析。
The potential utility of feed forward artificial neural network using the back propagation algorithm (BP-ANN), in interpreting pyrogram data from traditional Chinese medicine was discussed.
将以误差反向传播为训练算法的前馈式人工神经网络（BP- ANN）首次用于中草药的裂解气相色谱谱图解析。
应用推荐