MATLAB动态神经网络-时间系列预测

看了matlat中文论坛上的用动态神经网络预测时间序列

http://www.ilovem http:// a http:// http:// tlab.cn/thread-113431-1-1.html

（1）第一种基本知识需要知道

训练数据（training data）

验证数据（validation data）

测试数据（testing data）

这三个需要分清，可是我不是很明白。明白的，麻烦留个言解释下，谢谢啦。

下面是某个网站的对三者的解释：

http://stackoverflow.com/questions/2976452/whats-the-diference-between-train-validation-and-test-set-in-neural-networks?answertab=oldest#tab-top

The training and validation sets are used during training.

for each epoch    for each training data instance        propagate error through the network        adjust the weights        calculate the accuracy over training data    for each validation data instance        calculate the accuracy over the validation data    if the threshold validation accuracy is met        exit training    else        continue training

Once you're finished training, then you run against your testing set and verify that the accuracy is sufficient.

Training Set: this data set is used to adjust the weights on the neural network.

Validation Set: this data set is used to minimize overfitting. You're not adjusting the weights of the network with this data set, you're just verifying that any increase in accuracy over the training data set actually yields an increase in accuracy over a data set that has not been shown to the network before, or at least the network hasn't trained on it (i.e. validation data set). If the accuracy over the training data set increases, but the accuracy over then validation data set stays the same or decreases, then you're overfitting your neural network and you should stop training.

Testing Set: this data set is used only for testing the final solution in order to confirm the actual predictive power of the network.

（2）第二种基本只是需要知道

matlab自带的神经网络工具箱的时间序列预测中，有三种类型。

A有一个输入x(t),有一个输出y(t)。如：输出的关系y(t)=y(t-1)+y(t-2)+...y(t-d)+x(t-1)+x(t-2)+...+x(t-d)

B只有以输出。如输出y(t)=y(t-1)+y(t-2)+...+y(t-d)

C如y(t)=x(t-1)+x(t-2)+..+x(t-d)

（3）对于训练的结果

利用matlab神经网络时间序列预测的时候，需要不断调整numbers of hidden neurons 和number of delays d，

最后通过观察plot error autocorrelation和plot response两个重要的图，如果训练得好，

error autocorrelation是处于允许范围的误差内的，如果是A类型的还有一个plot inout-error correlation

对于这三种给我就是看视频有了个定性的判断，对于原理还是不懂。希望可以得到有缘人的指教。^_^

(4)预测部分

前期工作都已经做好，就剩下我们的目的，预测了。可惜的是，视频没有关于预测部分，不过视频主讲人还是

意识到这个问题，发了个帖子，对观众讲解了一点点预测的方法。

http://www.ilovematlab.cn/thread-132940-1-1.html

http://www.ilovematlab.cn/forum.php?mod=viewthread&tid=216264