Rules | Recent posts | topic RSS | Search | Register  | Log in

Neural network - prediction. How?

 
Post new topic  Reply to topic    EDAboard.com Forum Index -> Network
Author Message
ckck20



Joined: 19 May 2002
Posts: 37


Post22 Dec 2006 23:10   Neural network - prediction. How?

Hi,
i have a set of measurements(about 1000) about the intensity of the wind and these are taken at intervals of 10min on the same place. I need to predict the intensity of the wind for the next 2 hours(the new 12 measurements).
I don't know how to model this as a neural network. I mean, that i don't know what to use for the training(inputs and targets).
I'd like to hear your ideas and please anything is appreciated!

Thanks in advance
Back to top
mdanaie



Joined: 13 Oct 2004
Posts: 67
Helped: 5


Post23 Dec 2006 9:02   Neural network - prediction. How?
tags: nural network

The answere is so tricky
The best answere is to use 2 input nural network the first input is your data taken each 10 minutes. for the second input use the same data with 10 minutes delay. It means you have a Z^-1 feedback from output to input making the nural network able of predition. using a single or double feedback( Z^-1 and Z^-2) is usually enough.
Back to top
ckck20



Joined: 19 May 2002
Posts: 37


Post23 Dec 2006 12:58   Re: Neural network - prediction. How?

Thanks for your answer.
I'm using matlab and a backpropagation neural network. The training is done by giving it as input the last 10 measurements and targeting it to the next(assuming all i want is the n+1 prediction). But it doesn't learn!
Now i'll search about what you said and see what i can do.
Back to top
leekk8



Joined: 06 Sep 2005
Posts: 288
Helped: 13
Location: Malaysia


Post25 Dec 2006 15:45   Neural network - prediction. How?

As I think, the way you do it should work. Taking 10 last measurements instead of just 2, the result should be better. Anyway, you can modify your neural network and test with every kind of input and output.

Another thing you should put attention is the architecture of the neural network. How many hidden layers you're using? How many neurons on each hidden layer? Also make sure your neural network code is correct. You can try this by testing with XOR problem, which is a typical example of backpropagation neural network.
Back to top
ckck20



Joined: 19 May 2002
Posts: 37


Post27 Dec 2006 22:41   Neural network - prediction. How?

Hi, and thanks for your reply.
My code is correct as i see it. I'm using 1 hidden layer of about 10-20 neurons and i've tried using different number of past values. I noticed that i get better results when using 1 hidden layer instead of 2. But the overall prediction is not good in both cases. I've been trying for a day now to find the right combination but till now i haven't found it. Maybe i should use a different approach, but the one i used seems more logical to me. Any suggestions?
Back to top
leekk8



Joined: 06 Sep 2005
Posts: 288
Helped: 13
Location: Malaysia


Post16 Jan 2007 14:01   Neural network - prediction. How?

ckck20, how's your findings now? Can you get a good result?

As you have around 1000 data, I think you may need to input more instead of just 10...If you input 50 inputs, and predict the next data, it may work...you have to test out all the methods of input and output, beside the architecture of the neural network.
Back to top
Post new topic  Reply to topic    EDAboard.com Forum Index -> Network
Page 1 of 1 All times are GMT + 1 Hour


Abuse
Administrator
Moderators
topic RSS 
sitemap