通过神经网络进行时间序列预测

本文介绍了通过神经网络进行时间序列预测的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

最近我一直在为各种目的研究神经网络.我在数字识别，XOR和其他各种简单/您好的世界级应用程序中都取得了巨大的成功.

I have been working on Neural Networks for various purposes lately. I have had great success in digit recognition, XOR, and various other easy/hello world'ish applications.

我想解决时间序列估计的领域.目前，我没有大学帐户可免费阅读有关该主题的所有IEEE/ACM论文，也找不到许多使用ANN进行时间序列预测的资源.

I would like to tackle the domain of time series estimation. I do not have a University account at the moment to read all the IEEE/ACM papers on the topic (for free), nor can I find many resources detailing using ANN for time series forcasting.

我想知道是否有人有任何建议或可以推荐有关使用ANN通过时间序列数据进行预测的任何资源?

I would like to know if anyone has any suggestions or can recommend any resources concerning using ANN for forcasting via time series data?

我假设要训练NN，您将插入几个立即的时间步，而预期的输出将是下一个时间步(例如:n-5，n-4，n-3，n-2， n-1应该在时间步长N处输出结果....然后向下滑动一些时间步长，然后再次执行所有操作.

I would assume that to train the NN, you would insert a few immediately time steps and the expected output would be the next timestep (example: inputs of n-5, n-4, n-3, n-2, n-1 should come out with an output of result at timestep N. ... and slide down some amount of timesteps and do it all again.

任何人都可以确认或对此发表评论吗?我会很感激！

Can anyone confirm this or comment on it? I would appreciate it!

推荐答案

我认为您已经有了一个基本概念:一种滑动窗口"方法，其中网络被训练为使用序列的最后k个值(T nk ... T n-1 )来预测当前值(T n ).

I think that you've got the basic idea: a "sliding window" approach where a network is trained to use the last k values of a series (Tn-k ... Tn-1) to predict the current value (Tn).

但是，有很多方法可以执行此操作.例如:

There are a lot of ways you can do this, however. For example:

• 那个窗口应该有多大?
• 是否应该以任何方式对数据进行预处理(例如，去除异常值)?
• 应使用哪种网络配置(例如，隐藏节点数，层数)和算法?

通常人们最终会通过反复试验找出最好的方法来学习其特定数据.

Often people end up figuring out the best way to learn from their particular data by trial and error.

关于此类内容的公开信息很多.从这些开始，看看它们的引文和通过Google Scholar引用它们的论文，您应该有足够的内容阅读:

There are a fair number of publicly-accessible papers out there about this stuff. Start with these, and look at their citations and papers that cite them via Google Scholar, and you should have plenty to read:

• Frank，RJ和Davey，N.和Hunt，SP 时间序列预测和神经网络. 《智能与机器人系统杂志》，2001年.第31卷，第1期，第91-103页.
• J.T.康纳，R.D.Martin和L.E.地图集. 递归神经网络和稳健的时间序列预测. IEEE Transactions on Neural Networks，1994年3月.第5卷，第2期，第240-254页.

• Frank, R. J. and Davey, N. and Hunt, S. P. Time Series Prediction and Neural Networks. Journal of Intelligent and Robotic Systems, 2001. Volume 31, Issue 1, pp. 91-103.
• J.T. Connor, R.D. Martin, and L.E. Atlas. Recurrent neural networks and robust time series prediction. IEEE Transactions on Neural Networks, Mar 1994. Volume 5, Issue 2, pp. 240 - 254.