- Do I have to attend a workshops
No. You may also take part in the
competition and only submit your predictions. You can still win!
- Do I have to attend all workshops?
No. The idea is to offer you choices when & where to present.
- Can I win something?
We are currently talking to the conference organisers to source
additional funding for student submissions.
Are other methods allowed?
Yes, as long as they are methods of computational
Intelligence or computationally intensive (ridge regression, wavelets
etc.) Statistical methods may submit results as benchmarks (as they are
not CI methods) and will be evaluated against the computational methods!
We welcome submissions from statistical software vendors to demonstrate
the capabilities of their software, although they may not win the
- Do I have to forecast all
series with the same Neural Network setup?
No. The objective requires a single & consistent methodology, that
is implemented across all time series. This does not require you to
build a single neural network with a pre-specified input-, hidden and
output-node structure but allows you to develop a process in which to
run tests and determine a best setup for each time series. Hence you can
come up with different network architectures, fuzzy membership
functions, mix of ensemble members etc. for your submission. However,
the process should always lead to selecting the same final model
structure as a rigorous process. So if you - for example - wish to
differentiate between trended, seasonal and stationary time series in
model building you must develop a methodology that systematically test
each of the series in the same way to make successive decisions. You may
of course also use just a single neural network architecture to forecast
all time series identically. In other words, you must develop a
methodology than can be replicated by others, and would lead to
identical results on the same dataset.
For additional help please contact the workshop organisers
Sven F. Crone
Lancaster University Management School
Centre for Forecasting
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The Knowledge Portal on Forecasting with Neural Networks @ www.neural-forecasting.com - last update: 18.10.2006