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。
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。
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