It looks like you're new here. If you want to get involved, click one of these buttons!

- All Categories 2.2K
- Applied Category Theory Course 352
- Applied Category Theory Seminar 4
- Exercises 149
- Discussion Groups 49
- How to Use MathJax 15
- Chat 479
- Azimuth Code Project 108
- News and Information 145
- Azimuth Blog 149
- Azimuth Forum 29
- Azimuth Project 189
- - Strategy 108
- - Conventions and Policies 21
- - Questions 43
- Azimuth Wiki 711
- - Latest Changes 701
- - - Action 14
- - - Biodiversity 8
- - - Books 2
- - - Carbon 9
- - - Computational methods 38
- - - Climate 53
- - - Earth science 23
- - - Ecology 43
- - - Energy 29
- - - Experiments 30
- - - Geoengineering 0
- - - Mathematical methods 69
- - - Meta 9
- - - Methodology 16
- - - Natural resources 7
- - - Oceans 4
- - - Organizations 34
- - - People 6
- - - Publishing 4
- - - Reports 3
- - - Software 21
- - - Statistical methods 2
- - - Sustainability 4
- - - Things to do 2
- - - Visualisation 1
- General 39

Options

Neural Network Delta Forecast for El Nino 3.4 Anomalies

A bit improvement on the error in comparison to SVR's 9% reduced to 7.9% for NN, but the max deviation range was increased a bit.

**IMPORTANT: error for each of the 6 months was at the same level, not increasing as in the case of SVR**

3 Layers, Input and Hidden each of 37 length, in other words the training samples vectors of length 37.

Output layer of length 6, for next 6 months forecasts.

300 sweeps of entire data, each step repeated 30 times, total of 9000 learning sessions.

Dara

## Comments

John

I assume N in NIPS is for Neural Networks. So I did this forecast for you to be on the safe side. Also I wanted to make sure the SVR results are not off.

`John I assume N in NIPS is for Neural Networks. So I did this forecast for you to be on the safe side. Also I wanted to make sure the SVR results are not off.`

Code written in C, fully parallelized on 16 cpu server via Intel's OPENMP compiler technology.

`Code written in C, fully parallelized on 16 cpu server via Intel's OPENMP compiler technology.`

Hello John

This algorithm assumes smooth functions and the manipulation of the error terms has calculus background to them.

Another version of this algorithm could be obtained for continuous functions which are not smooth, and no calculus smooth operators needed.

In this case the error term will be minimized by a global minimizer e.g. Differential Evolution and that could run might fast on the new GPU servers.

Dara

`Hello John This algorithm assumes smooth functions and the manipulation of the error terms has calculus background to them. Another version of this algorithm could be obtained for continuous functions which are not smooth, and no calculus smooth operators needed. In this case the error term will be minimized by a global minimizer e.g. Differential Evolution and that could run might fast on the new GPU servers. Dara`

I will go thru the code this week and thoroughly test everything to make sure results are as accurate as possible

`I will go thru the code this week and thoroughly test everything to make sure results are as accurate as possible`