Discussion of article "Genetic Algorithms - It's Easy!"

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New article Genetic Algorithms - It's Easy! is published:

In this article the author talks about evolutionary calculations with the use of a personally developed genetic algorithm. He demonstrates the functioning of the algorithm, using examples, and provides practical recommendations for its usage.

Author: Андрей

 

IMHO this article is a great contribution, but the title underestimates the content. I suspected to find a simple introduction to GA but I got already developed library to work with. Thanks!

 

On health! :)

PS Yes, and still. If I article named: "Genetic algorithms it is very difficult!", who would read it?. :)

Though also it would not correspond to true. Nevertheless, GA are simple if a little to make efforts judgement. As however, everything demands judgement, as to the markets. If we want to earn on them...

PPS I warn at once, now and subsequently I will use machine translation means. I am sorry.
 
The important remark to article.

Do not use algorithm parametres

FFNormalizeDigits and GeneNormalizeDigits

It is not necessary to normalise value of fitness function and genes. Normalisation leads to decrease in search ability of algorithm and increase in quantity of starts FF. And, the more signs after a comma it is rejected, the negative influence on algorithm is more strongly shown.

In other words introduction of operation of normalisation in algorithm was an error.

Not to confuse to operation of digitization operated in parametre Precision!
 
Update Library UGA and examples for this article. Current free authoring version 1.2.1.

Files:
ugalib_v1.2.1_eng.zip  12 kb
 
Update Library UGA and examples for this article. Current free authoring version 1.3.0.

Files:
ugalib_ru.zip  56 kb
ugalib_eng.zip  57 kb
 
Update Library UGA and examples for this article. Current free authoring version 1.3.1.

Files:
ugalib_ru.zip  56 kb
ugalib_eng.zip  56 kb
 

Great article! Thank you. 

As I can see you wanted to use UGA for optimizing the training of NNs. Was it successful? What were the genes of the chromosome in this case? Have you developed your own NN library as well or have you found any existing NN implementation supporting the integration with MT5 and GA?


 

 
zsazsa:

Great article! Thank you. 

1) As I can see you wanted to use UGA for optimizing the training of NNs. Was it successful?

2) What were the genes of the chromosome in this case?

3) Have you developed your own NN library as well or have you found any existing NN implementation supporting the integration with MT5 and GA?

1) Yes.
2) Weights and biases of neurons of a network I represent as chromosome genes.
3) I have written own realization of a neural network.
 

Is it possible for you to post an example how you would use this library to optimize an Expert advisor like the way MT does?

 

It would be a great help for me

Thank you 

 
moosa:

Is it possible for you to post an example how you would use this library to optimize an Expert advisor like the way MT does?

It would be a great help for me

Thank you 

To make the library work like the way MT does for EA, have a lot to build upon: calculate orders, the calculation of equity and balance and much more.
I, unfortunately, there is no time for it, and the stimulus....
Maybe later.
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