CMAC (Cerebellar Model Articulation Controller) is a kind of local learning feed - forward neural network with simple architecture, quick learning convergence and effective implementation.
小脑模型清晰度控制器(CMAC)是一种局部学习前馈网络，结构简单，收敛速度快，易于实现。
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。
This paper presents a kind of software faults prediction model based on artificial neural network and the structure of the feed-forward multi-layer network with backpropagation learning algorithm.
该文介绍了一种基于人工神经网络的软件失效预测模型，给出了基于反向传播算法的多层前向网络的网络结构。
This paper presents a kind of software faults prediction model based on artificial neural network and the structure of the feed-forward multi-layer network with backpropagation learning algorithm.
该文介绍了一种基于人工神经网络的软件失效预测模型，给出了基于反向传播算法的多层前向网络的网络结构。
应用推荐