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。
With the support of GIS and RS, efforts were made to develop a quantitative analysis model of urban spatial thermal environment based on genetic algorithms back propagation and genetic algorithms.
针对以往空间热环境分析模型的不足,在遥感、地理信息系统支持下,创建了基于人工神经网络和遗传算法的城市热环境非线性定量分析模型。
There are a few training algorithms for parameter estimation of neural networks, in which Back Propagation(BP)algorithm is the typical algorithm for feed-forward multi-layer neural networks.
神经网络参数估计有许多训练算法,BP算法是前向多层神经网络的典型算法,但BP算法有时会陷入局部最小解。
Finally, several example simulations are made to compare our algorithms with traditional error back propagation, simple weight decay, and relative methods in other paper.
最后通过大量实例仿真将它们与纯误差驱动的方法、权退化法、其它文献中的相关方法进行了比较。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
结合遗传算法(GA)和误差反馈型神经网络(BP),建立了优化的GA - BP神经网络预测模型,预测转炉炼钢过程钢液终点磷含量。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
结合遗传算法(GA)和误差反馈型神经网络(BP),建立了优化的GA - BP神经网络预测模型,预测转炉炼钢过程钢液终点磷含量。
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