Prevent ANFIS from negative or unrealistic outputs
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Hi all, I'm using ANFIS in order to forecast load values based on several inputs. However, many outputs are negative or sometimes very high valued and the accuracy is very bad. It is to be noted, that nor negative neither high values are included in the learning data.
I tried several things to address these problems, e.g. - preprocessing of the inputs - enlarge or shrink the learning data - adapting learning algorithm - adapting and/or methods - ...
Whatever I did, the outputs didn't get any better. I am aware of the fact, that the curve to predict is highly fluctuating and therefore a very complex case for ANFIS. Nevertheless, I hope to improve my results with further adaptions.
Has anyone any idea? I'm rather helpless at this point and really really stuck.
Thank you very much in advance! Martin
Risposte (4)
Martin
il 28 Mar 2012
0 voti
Win co
il 20 Apr 2012
0 voti
Firstly, I'm sorry about not replying soon because this forum has not sent me notification of your comment. Secondly, your link seems not downloadable. Thirdly, could you show us the figures of training and checking phase ? Regards, Winn
Harry
il 7 Set 2013
0 voti
Hello,
i have exactly the same problem as Martin described above. Does anyone know how to solve the problem?
Thank you very much for your answer!
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