The model and learning algorithms of BP( Error Back Propagation)network, which is widely applied, is recommended, and RBF( Radial B asis Function)is simply recommended contrastively.
本文首先介绍了神经网络中应用最为成熟广泛的BP网络的模型及其学习算法，并简单对比介绍了RBF网络。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
A neural network model with dynamical compensating capability is analyzed. During the training of this network model, we apply the principle of dynamic error back-propagation.
本文分析了一种动态补偿神经网络模型，模型的训练利用反向传播原理实现。
The new model was based on the weight adjustments of error back propagation of BP algorithm and the weight modification using particle swarm optimization (PSO).
提出一种基于粒子群算法优化BP网络的权值调整新方法。
The new model was based on the weight adjustments of error back propagation of BP algorithm and the weight modification using particle swarm optimization (PSO).
提出一种基于粒子群算法优化BP网络的权值调整新方法。
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