For the shortages of the method in which network flux is predicted by forward neural network based on traditional BP algorithm, a 2-level network flux predict-adjust model is constructed.
针对基于传统BP算法的前向神经网络预测网络流量方法的不足，构建了一种二级的网络流量预测-校正模型。
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。
Some alteration were made on structure and training algorithm for traditional serial fuzzy BP neural network.
本文对传统的串联型模糊bp网络进行了结构和训练算法上的部分改进。
应用推荐