Discussing the article: "Population optimization algorithms: Evolution of Social Groups (ESG)" - page 3

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tanner gilliland genetic algorithm. I was wondering if you could help me get your BGA optimisation working. I have been looking at some of your articles on this topic. However, I feel like I am starting late, missed some information somewhere and don't know how to actually optimise the EA with a different algorithm. I downloaded and compiled test_ao_bga.mq5. When I load the terminal it says: "Invalid programme type, loading Test_AO_BGA.ex5 failed". If I try to run it, the terminal reports "Test_AO_BGA.ex5 not found". Could you please help me to get it to work? And how do I configure my own EA to use BGA optimisation? Thanks.

Try selecting a different compilation mode:

There is an article on "How to use optimisation algorithms".

Использование алгоритмов оптимизации для настройки параметров советника "на лету"
Использование алгоритмов оптимизации для настройки параметров советника "на лету"
  • www.mql5.com
В статье рассматриваются практические аспекты использования алгоритмов оптимизации для поиска наилучших параметров советников "на лету", виртуализация торговых операций и логики советника. Данная статья может быть использована как своеобразная инструкция для внедрения алгоритмов оптимизации в торгового советника.
 
Andrey Dik # :

Try choosing a different compilation mode:

There is an article on the topic "How to use optimisation algorithms" .

Thank you.

 
Andrey Dik # :

Try choosing a different compilation mode:

There is an article on the topic "How to use optimisation algorithms".

I managed to get it to work, so thanks again. I have one more question if you don't mind me asking it. In your experience, are your alternative genetic algorithms able to perform well even with very large amounts of input data? I have a small neural network advisor with two layers and 176 weights. When I optimise all the weights, the number of possible input combinations is huge. (up to 9^176 or 8.8e+167). Do you think he will still find a good solution (if not the best)?

 
tanner gilliland #:

I managed to get it to work, so thanks again. I have one more question if you don't mind me asking it. In your experience, are your alternative genetic algorithms able to perform well even with very large amounts of input data? I have a small neural network advisor with two layers and 176 weights. When I optimise all the weights, the number of possible input combinations is huge. (up to 9^176 or 8.8e+167). Do you think he will still find a good solution (if not the best)?

yes
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