if you are using Matlab, the Neural Network Toolbox comes with an excellent user's guide. Follow the examples and reading the user guide can give you a pretty good understanding of Forecasting with NN.

Prof Crone has given you a very good link. Here are some others you may use.

http://arxiv.org/abs/1302.6613

HI 

I hope the following papers will be helpful. 

Best Wishes

There is a lot of literature on ANN related to forecasting.

Here are a couple of links that you might find useful.  The first is a series of slides, while the second contain (in addition to links to some other tutorials, some data on which you may choose to work).

http://www.neural-forecasting.com/Downloads/EVIC05_tutorial/EVIC%2705%20Slides%20-%20Forecasting%20with%20Neural%20Networks%20Tutorial%20SFCrone.pdf

http://www.neural-forecasting.com/tutorials.htm

Hi Debora. The website www.neural-forecasting.com which I setup some years ago (and which Partha Dey kindly referenced) unfortunately ran out of funding and is now no longer updated - so I am afraid that they are quite old! (PS. we hope to get funding again and will then revive the website ....)

For more current developments, please see the papers on forecasting with neural networks please see my papers (many are here on research gate or http://www.lancaster.ac.uk/lums/people/all/sven-crone/ or www.sven-crone.com). If you can let us know the actual application then we can give some more detailed feedback, as the setup variies quite a bit between forecasting hourly electricity load data versus monthly industry productsion.

Hope this helps, Sven

if you are using Matlab, the Neural Network Toolbox comes with an excellent user's guide. Follow the examples and reading the user guide can give you a pretty good understanding of Forecasting with NN.

Prof Crone has given you a very good link. Here are some others you may use.

http://arxiv.org/abs/1302.6613

dear friend

you may look at some of my publications:

Mandal, I., Sairam, N. New machine-learning algorithms for prediction of Parkinson's disease (2014) International Journal of Systems Science, 45 (3), pp. 647-666. DOI: 10.1080/00207721.2012.724114

Mandal, I., Sairam, N. Accurate telemonitoring of Parkinson's disease diagnosis using robust inference system (2013) International Journal of Medical Informatics, 82 (5), pp. 359-377. DOI: 10.1016/j.ijmedinf.2012.10.006

Mandal, I., Sairam, N. Accurate prediction of coronary artery disease using reliable diagnosis system (2012) Journal of Medical Systems, 36 (5), pp. 3353-3373. DOI: 10.1007/s10916-012-9828-0

Mandal, I., Sairam, N. Enhanced classification performance using computational intelligence (2011) Communications in Computer and Information Science, 204 CCIS, pp. 384-391. DOI: 10.1007/978-3-642-24043-0_39

Mandal, I. Software reliability assessment using artificial neural network (2010) ICWET 2010 - International Conference and Workshop on Emerging Trends in Technology 2010, Conference Proceedings, pp. 698-699. DOI: 10.1145/1741906.1742067

Mandal, I. A low-power content-addressable memory (CAM) using pipelined search scheme (2010) ICWET 2010 - International Conference and Workshop on Emerging Trends in Technology 2010, Conference Proceedings, pp. 853-858. DOI: 10.1145/1741906.1742103

Mandal, I. A novel approach for accurate identification of splice junctions based on hybrid algorithms (2014) Journal of Biomolecular Structure and Dynamics

pp. 1-10 | DOI: 10.1080/07391102.2014.944218 PMID: 25203504 http://www.tandfonline.com/eprint/TzMeXxpEXxujtEATHwqY/full

Thank you,

Best regards

Dr.Indrajit Mandal

I am examining every source you have indicated.

Many thanks to you all.

@Mandal: your answer is unfortunately misleading as all the resources you point to are on classification or other tasks, but not related to forecsting (i.e. predicting an interval or metric scaled variable = regaression, often using time series of observations). Please try to be careful not to give misleading answers. Best wishes, Sven