Neural Network Software Free

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Attachments: Finally! a REAL Neural Network EA Free - Something New

Free Neural Network Software For Windows
Neural Network Software Free Download
Neural Network Software Reviews

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First Post:Edited Oct 23, 2014 9:26amMar 7, 2013 7:50pm EditedOct 23, 2014 9:26am

Commercial MemberJoined Sep 2008908 Posts

Hello Everyone, it's been a while. I usually don't take such long breaks from participating on this forum but for over a year I've been working on a very intensive project and after a year of forward testing I'm here to share it with all of you.
I'm friends with many professional traders and a bunch of us got together, combined our expertise and created a neural network automated system for Metatrader that actually works. Since we're aware that most EAs are absolutely worthless or worse, scams, we thought we'd be providing something unique to the average retail trader from people who can actually be trusted. This group is called Metaneural.
We've used neural networks and applied them to trading Forex successfully in the past and decided to translate that method into a Metatrader system. It is widely known that the larget trading firms and hedge funds use sophisticated artificial intelligence and nueral network systems to profit from the financial markets with staggering accuracy. We thought, why can't that power also be available to us - the small money investors?
So I took a break from all my other activities and worked hard with Metaneural to develop this system, which I believe to be the only REAL neural network EA. In fact, it doesn't even have to be an EA, the code can be written in C++ to work exactly the same way in tradestation, esignal, neuroshell, or any platform that allows DLL importing and data gathering, because the neural network creation happens in Neurosolutions.
I've made indicators and trading systems for the forexfactory community for years so I wanted to give you guys the only free version of the Metaneural EA on the internet. I want to get your feedback and impressions. If this thread goes well and doesn't get sidetracked I'll extend the trial. I've had fun deciphering the forex market with the great minds on this forum for years and it is my pleasure to give back. Neural networks in EAs is the future, I hope you guys can realize this and develop your own systems.
HOW IT WORKS
Data Colletion
The first step in creating an artifical neural network brain is to gather the data around which the structure of the brain will be formed. Since we are trying to create a brain that will know how to trade the markets we must gather market data.
http://www.metaneural.com/img/previe..on-pattern.png
However, we cannot simply collect a mass of data and dump it into our neural engine to create the structure of our brain. We must gather the data in the format which we want the brain to process that data and eventually the same format we want it to create output in. In other words, we're not only telling our brain WHAT to think, by giving it raw data, but we must tell it HOW to think, by formulating that raw data into an intelligable configuration.
In this case, our intelligible configuration is patterns. We gather data in segments, each segment consists of a number of bars set by the trader in our proprietary collection indicator which comes with all of our packages. That grouping of bars is collected in relation to the next bar that comes after the grouping - we will call this the future bar. When we're collecting market data the future bar is known, because it is all historical data, it is the next bar after the grouping. The idea is that the neural network brain will find complex patterns in the bar grouping and use the information collected, including the 'next bar' after the grouping, to determine which complex patterns preceed the result of the next bar. During actual trading that result will be the future bar which in effect makes it possible to know with a high degree of accuracy the direction of the market before it happens.
http://www.metaneural.com/img/preview/csv.png
The collected data is extracted into a spreadsheet which displays price data as open, high, low, close (OHLC). The OHLC of each bar is collected separately and placed in its own column. In the example above each row represents 3 bars in total. Therefore, the columns represent hundreds or thousands of bars collected going back into history.In addition to OHLC you can also collect the values from almost any indicator you select, which will essentially give that indicator the ability to 'think' based on changing market conditions and predict the next value.
Neural Network Building and Training
Now that we have our collected data, extracted into a spreadsheet file in an intelligible configuration, we can load it into our neural network engine which will create the structure of the artifical brain, train it, and test its accuracy before saving the structure.
http://www.metaneural.com/img/preview/inputs2.png
Once the collected data is imported into the network building program you are given the choice to select which bits of data you want to use to build your brain. This is an important feature because it enables the user to create many different strategies based on whichever piece of data is deemed necessary. What we're essentially doing in this step is determining what the engine will use to create the complex patterns mentioned earlier, which will ultimately decided the projection ability of the neural network EA.
For example, say you wanted to tell the neural network to only look for patterns in the open prices of bars in relation to the indicator values from your favorite indicator. You would then select your indicator in the collector and choose only the open and data inputs in the building software depicted above. You can also select all the inputs, except for the output1 column, which signifies your output value - selecting all inputs will create the most complex learning pattern possible and thereby allow your brain to respond to many different scenarios.
http://www.metaneural.com/img/preview/train.png
Once the desired inputs and outputs are selected the software will create the structure of your neural network brain and you can begin to train it. A portion of the collected data is set aside and used to train and test the accuracy of your artificial brain, you will see the desired output begin to conform to the testing data as it 'learns'. Once this process is complete you will be able to export the structured artificial brain in the form of a DLL which will be used by the MetaNeural EA.
EA Implementation
Once the brain is built, trained, tested, and exported as a DLL you can begin trading with an automated neural network brain that will see complex patterns that are impossible for a human to achieve.
Get the Metaneural EA FREE now by funding an account at FinFX with any amount and using our trade copier service to mirror our professional winning trades in your account. After 50 full lots are traded you will receive the Metaneural EA with full functionality for FREE!
Accounts must be funded with the link provided in the pricing section of the Metaneural site.
http://widgets.myfxbook.com/widgets/1046597/large.jpg
Place these files in the following folders in Metatrader:
Expert Advisor - Metatrader 4experts
Collector Indicator (DatacollectorV2a) - Metatrader 4expertsindicators
Neural Network Indicator (Metaneural NN Indicator) - Metatrader 4expertsindicators
MQLLock and MT4NSAdapter DLL files - Metatrader 4expertslibraries
You will need to install Neurosolutions 6 and Visual Studio 6 for it work, instructions on these installations can be found in the very detailed Manual attached to this post.
YOU MUST READ THE MANUAL

showmycid.zip 12 KB 5,599 downloads Uploaded Mar 10, 2013 5:17am

Indicators and Libraries.zip 5.5 MB 9,562 downloads Uploaded Mar 14, 2013 8:18am

MetaNeural_EA_v218-rev2.ex4 126 KB 7,088 downloads Uploaded Mar 14, 2013 8:18am

Joined Dec 2010Status: Member18,740 Posts

Hi FOREXflash
an interesting work.
as you also now, you are startig a long jurney here
will be watching
good luck

Joined Dec 2011Status: Member6 Posts

Hi
Do you have a trackrecord/performance that you could share with us. I see one on MyFxBook, the name is MetaNeural EA 2013, it is nothing exciting. They say on the website that they expect 30% gains in a year, which is something a good manuel trader can produce in a month. And their Average Loser is 6 times the Average Winner, which is terrible trading in my book whenever Average Winner is not greater than the Avg Loser, regardless of the Win Ratio.
http://www.myfxbook.com/members/meta..ea-2013/492969
Please advise
Thanks

Commercial MemberJoined Sep 2008908 Posts

This is the trading results from 2012 - 2013, it is on the main site: http://www.myfxbook.com/members/meta..ural-ea/484469

Commercial MemberJoined Jan 201332 Posts

Congratulations on developing a system which gives healthy returns. Always better than wonder EAs which usually end up blowing the account.
I am a commercial member myself sharing my Fibonacci Makeover system (ForexFibs.com) here so I can understand why you are offering a Free EA.
My question is can this EA be applied to multiple currencies as it is based on Real Neural Networks? Is it dependent on broker and execution speed?
Thanks

Commercial MemberJoined Sep 2008908 Posts

Hello iowntam,
Yes, it can be applied to multiple currencies simultaneously because it can be trained on each currency individually and a neural network structure can be created for each currency. I would say the only broker dependency would be the integrity of their price feed, the more stable and consistent their feed the better the training data will be and subsequently the trades. We're not scalping necessarily so execution speed is not very important. Thanks for your interest.

Free Neural Network Software For Windows

Mar 10, 2013 5:15amMar 10, 2013 5:15am

Joined Aug 2007Status: Doing It In Dubai2,414 Posts

Flash, just can't seem to get the showmycid tool, MQLLOck site seems to be having problems and gives the error 'Database error' Can you please post it here?

Edited at 9:23amMar 10, 2013 5:18am Editedat 9:23am

Commercial MemberJoined Sep 2008908 Posts

It is now attached to the first post, PM me the code it generates and I'll activate your trial - 7 days.

Flash, just can't seem to get the showmycid tool, MQLLOck site seems to be having problems and gives the error 'Database error' Can you please post it here?

Mar 10, 2013 5:35amMar 10, 2013 5:35am

Joined Aug 2007Status: Doing It In Dubai2,414 Posts

It is now attached to the first post, PM me the code it generates and I'll activate your trial - 15 days.

Thanks, sending you a pm now.

Mar 11, 2013 11:05amMar 11, 2013 11:05am

Commercial MemberJoined Sep 2008908 Posts

For those interested users who are downloading the EA - It will not work without the cid code, please run the cid app on your computer and send me the code to activate the EA. Regards.

Mar 12, 2013 12:20pmMar 12, 2013 12:20pm

Commercial MemberJoined Sep 2008908 Posts

Follow our live test and PM me with your codes before this trial period is concluded:
http://widgets.myfxbook.com/widgets/492969/large.jpg

Apr 9, 2013 12:20amApr 9, 2013 12:20am

Joined Apr 2013Status: Junior Member1 Post

hi.
firstly thank you for this information. Info that i really would like to put to the test.
secondly im new to this site so have not attained certain priviledges. therefore i am unable to pm you. how do i go about sending you my cid?

May 6, 2013 9:17amMay 6, 2013 9:17am

Fxflash, congrats on the work. I intend to test it soon, if you allow.
i noticed that the EA has many options regarding configuration, allowing the user to personalize it. I wonder if you guys provide a config that will work initially and if you update it along the time as needed. Also, if this part is solely in the user or he can rely on you guys to do it.
Thanks,
Rodrigo Samico.

Jul 21, 2013 2:18amJul 21, 2013 2:18am

ForexFlash: i am wondering do you use Nomlinear autoregressive with or with or without exogenous input ?
exogenous input can be one or two indicator or time of day ..
How does the data are proceced aka normalized : dou you use as input Price[t]..Price[0] or Price[t]-Price[t-1],.. or log(Price[t]-Price[t-1]),..

Jul 26, 2013 9:30pmJul 26, 2013 9:30pm

Joined Jul 2013Status: Junior Member1 Post

Hello,
I have downloaded everything, installed programs, and am very much looking forward to try out your hard work. Unfortunately as a new member I cannot send PM with my ID (52D283EAFFA54C4502440ECA59B40D5C) so, any solution ?
Thank for your help.
JBR

Aug 25, 2013 12:40pmAug 25, 2013 12:40pm

HI
I also would like to try this NN
this is my code 1D095AE8366DA0AA0A3068384F01FA37
Can you please activate
Ric Ver

Oct 22, 2013 6:06amOct 22, 2013 6:06am

Joined Sep 2012Status: Junior Member2 Posts

I also would like to try this N n
my code is 0E73A1D803AF025C148885F3AFEFC38A

Oct 25, 2013 6:26amOct 25, 2013 6:26am

sounds interesting. I'd like to try the training and see what it's lke
C1F124F6DD4D2F4B24D84ABC0E25EB48

Oct 27, 2013 7:46pmOct 27, 2013 7:46pm

Joined Oct 2013Status: Member12 Posts

AE9FF191D92EAD6D806B5D32E490C100
kindly activate the lisence

Nov 16, 2013 5:31pmNov 16, 2013 5:31pm

I would like to ask you to activate this ID
3CA1C82A6704332B53777CD78C74ECBC
Thanks.

Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning.

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1Simulators
2Development environments
- 2.1Component based
4Standards

Simulators[edit]

Neural network simulators are software applications that are used to simulate the behavior of artificial or biological neural networks. They focus on one or a limited number of specific types of neural networks. They are typically stand-alone and not intended to produce general neural networks that can be integrated in other software. Simulators usually have some form of built-in visualization to monitor the training process. Some simulators also visualize the physical structure of the neural network.

Research simulators[edit]

SNNS research neural network simulator

Historically, the most common type of neural network software was intended for researching neural network structures and algorithms. The primary purpose of this type of software is, through simulation, to gain a better understanding of the behavior and the properties of neural networks. Today in the study of artificial neural networks, simulators have largely been replaced by more general component based development environments as research platforms.

Commonly used artificial neural network simulators include the Stuttgart Neural Network Simulator (SNNS), Emergent and Neural Lab.

In the study of biological neural networks however, simulation software is still the only available approach. In such simulators the physical biological and chemical properties of neural tissue, as well as the electromagnetic impulses between the neurons are studied.

Commonly used biological network simulators include Neuron, GENESIS, NEST and Brian.

Data analysis simulators[edit]

Unlike the research simulators, data analysis simulators are intended for practical applications of artificial neural networks. Their primary focus is on data mining and forecasting. Data analysis simulators usually have some form of preprocessing capabilities. Unlike the more general development environments data analysis simulators use a relatively simple static neural network that can be configured. A majority of the data analysis simulators on the market use backpropagating networks or self-organizing maps as their core. The advantage of this type of software is that it is relatively easy to use. Neural Designer is one example of a data analysis simulator.

Simulators for teaching neural network theory[edit]

When the Parallel Distributed Processing volumes^[1]^[2]^[3] were released in 1986-87, they provided some relatively simple software. The original PDP software did not require any programming skills, which led to its adoption by a wide variety of researchers in diverse fields. The original PDP software was developed into a more powerful package called PDP++, which in turn has become an even more powerful platform called Emergent. With each development, the software has become more powerful, but also more daunting for use by beginners.

In 1997, the tLearn software was released to accompany a book.^[4] This was a return to the idea of providing a small, user-friendly, simulator that was designed with the novice in mind. tLearn allowed basic feed forward networks, along with simple recurrent networks, both of which can be trained by the simple back propagation algorithm. tLearn has not been updated since 1999.

In 2011, the Basic Prop simulator was released. Basic Prop is a self-contained application, distributed as a platform neutral JAR file, that provides much of the same simple functionality as tLearn.

In 2012, Wintempla included a namespace called NN with a set of C++ classes to implement: feed forward networks, probabilistic neural networks and Kohonen networks. Neural Lab is based on Wintempla classes. Neural Lab tutorial and Wintempla tutorial explains some of these clases for neural networks. The main disadvantage of Wintempla is that it compiles only with Microsoft Visual Studio.

Development environments[edit]

Development environments for neural networks differ from the software described above primarily on two accounts – they can be used to develop custom types of neural networks and they support deployment of the neural network outside the environment. In some cases they have advanced preprocessing, analysis and visualization capabilities.^[5]

Component based[edit]

PeltarionSynapse component based development environment.

A more modern type of development environments that are currently favored in both industrial and scientific use are based on a component based paradigm. The neural network is constructed by connecting adaptive filter components in a pipe filter flow. This allows for greater flexibility as custom networks can be built as well as custom components used by the network. In many cases this allows a combination of adaptive and non-adaptive components to work together. The data flow is controlled by a control system which is exchangeable as well as the adaptation algorithms. The other important feature is deployment capabilities.

With the advent of component-based frameworks such as .NET and Java, component based development environments are capable of deploying the developed neural network to these frameworks as inheritable components. In addition some software can also deploy these components to several platforms, such as embedded systems.

Component based development environments include: PeltarionSynapse, NeuroDimensionNeuroSolutions, Scientific SoftwareNeuro Laboratory, and the LIONsolver integrated software. Free open source component based environments include Encog and Neuroph.

Criticism[edit]

A disadvantage of component-based development environments is that they are more complex than simulators. They require more learning to fully operate and are more complicated to develop.

Custom neural networks[edit]

The majority implementations of neural networks available are however custom implementations in various programming languages and on various platforms. Basic types of neural networks are simple to implement directly. There are also many programming libraries that contain neural network functionality and that can be used in custom implementations (such as tensorflow, theano, etc., typically providing bindings to languages such as python, C++, Java).

Standards[edit]

In order for neural network models to be shared by different applications, a common language is necessary. The Predictive Model Markup Language (PMML) has been proposed to address this need. PMML is an XML-based language which provides a way for applications to define and share neural network models (and other data mining models) between PMML compliant applications.

PMML provides applications a vendor-independent method of defining models so that proprietary issues and incompatibilities are no longer a barrier to the exchange of models between applications. It allows users to develop models within one vendor's application, and use other vendors' applications to visualize, analyze, evaluate or otherwise use the models. Previously, this was very difficult, but with PMML, the exchange of models between compliant applications is now straightforward.

PMML consumers and producers[edit]

A range of products are being offered to produce and consume PMML. This ever-growing list includes the following neural network products:

R: produces PMML for neural nets and other machine learning models via the package pmml.
SAS Enterprise Miner: produces PMML for several mining models, including neural networks, linear and logistic regression, decision trees, and other data mining models.
SPSS: produces PMML for neural networks as well as many other mining models.
STATISTICA: produces PMML for neural networks, data mining models and traditional statistical models.