Based on error back propagation (BP) arithmetic, many improvements are put forward because of its disadvantages.
在误差反向传播(BP)算法的基础上，针对其不足提出了多种改进算法。
Chapter two describes the basic knowledge of ANN and BP (Error Back Propagation), and how to use in MATLAB.
第二章介绍了神经网络和BP网络的基础知识，及在MATLAB中的应用方法。
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。
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。
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。
应用推荐