其主要思想就是依据数据包的到达速率自适应地调整标记概率。
The main idea of it is adaptively adjust the marking probability of BLUE according to the arriving rate of packets.
本文提出了一种改进的BP算法，该算法基于黄金分割法自适应调整网络学习速率。
This paper presents an improved BP algorithm, which can adapt learning rate using gold-segmentation.
我们首先简单介绍基于累积误差的梯形下降法，在此基础上，给出了一种自适应学习速率的调整方案。
First, we introduce the trapezoid drop method based on cumulative error, and give a study way of adaptation.
为了提高网络的分类效果以及训练速度，采用了附加动量法和自适应学习速率调整法对BP算法进行了改进。
To improve the networks'classification effect and train speed, the additive momentum and self-adaptive–study-rate adjustment method are adopted further to improve traditional BP algorithm.
为了提高网络的分类效果以及训练速度，采用了附加动量法和自适应学习速率调整法对BP算法进行了改进。
To improve the networks'classification effect and train speed, the additive momentum and self-adaptive–study-rate adjustment method are adopted further to improve traditional BP algorithm.
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