Neural Network Stock Forecasting

This add-in to the PSO Research toolbox (Evers 2009) aims to allow an artificial neural network (ANN or simply NN) to be trained using the Particle Swarm Optimization (PSO) technique (Kennedy, Eberhart et al. 2001).This add-in acts like a bridge or interface between MATLABd-deOaos NN toolbox and...

The attached zip file contains what is needed to implement a two layer neural network. This will hopefully be the first part of a broader collection of neural network tools.It can be used to train and simulate a NN with two layers, an input layer and an output layer. The output layer's activation...

This is a learning model for matrix-based data. It can be more efficient than standard vector-based models when the training sample is small or the inputs are matrices, since this model has less parameters than standard ones and exploits an inner structure of the inputs. This model can be...


Platforms: Matlab

OptimuStock is the new generation of intelligent forecasting software based on neural network technology. Don™t be intimidated by these terms. You don™t need to be an expert in artificial intelligence to use our software. In just 3 clicks, you can start to predict the stock prices....


Platforms: Windows

User-friendly (see screenshot) Minimum knowledge of neural net technology Number of inputs and outputs are limited only by MS Excel limitation Can accommodate more than 2 outputs nodes. Most commercial available software is limited to one output node MS Excel graphing and data...


Platforms: Windows

NeuroXL Package is a neural network toolkit for Microsoft Excel. It consists of NeuroXL Predictor and NeuroXL Clusterizer. NeuroXL Predictor add-in is a neural network forecasting tool that quickly and accurately solves forecasting and estimation problems in Microsoft Excel. It is designed...


Platforms: Windows, Windows 8, Windows 7, Windows Server

Neural network poker is a Texas Hold 'Em program with the option to add a player controlled by a neural network. This program is in alpha stage so there are still some bugs and unimplemented features...


Platforms: Mac

Inspired by neurons and their connections in the brain, neural network is a representation used in machine learning. After running the back-propagation learning algorithm on a given set of examples, the neural network can be used to predict outcomes for any set of input values. Neural Networks...


Platforms: Windows

This code implements the basic back propagation of error learning algorithm. the network has tanh hidden neurons and a linear output neuron, and applied for predicting y=sin(2pix1)*sin(2pix2).We didn't use any feature of neural network toolbox.


Platforms: Matlab

-Compatible with pre-2010 vers. of Matlab and Neural network toolbox-Trains a perceptron for the spring and one for the damper. -Runs a simulation with forcing function and noise.-If you don't have the toolbox, you can still use my back-propagation.


Platforms: Matlab

Again I'm uploading my homework...This is a GUI which enables to load images and train a Hopfield network according to the image.You can run the network on other images (or add noise to the same image) and see how well it recognize the patterns.Hopfield neural networks simulate how a neural...


Platforms: Matlab

Comprehensive system for stock market traders and investors, consists of the 5 modules. Technical indicators processor determines which indicator should be trusted more for particular market conditions and specific shares using back-testing simulation. It composes the forecast from indicators...


Platforms: Windows, Windows 7, Windows Server

Your data is imported into a grid and used to train a neural network. The input values are forced to swing beyond their limits. The output values are forecasted by the neural network. A new neural network is created using the new inputs and forecasted outputs. The neural networks are...


Platforms: Windows

This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more...


Platforms: Matlab

EasyNN-plus is a neural network system for Microsoft Windows. It makes the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files and images. The user can produce training, validating and querying files using the facilities in...


Platforms: Windows

annie stands for Artificial Neural Network Library and is a C++ API (library) for neural network training and execution. ersions exist for both Windows and flavours of Unix (tested on Linux). The library currently has support for training, saving and executing multi-layer perceptron,...


Platforms: *nix

ffnet is meant to be an easy and fast feed-forward neural network training solution for python..


Platforms: *nix

MIDI Data Miner uses a neural network to learn correlations between notes and control changes in a MIDI file. After training MDM can augment a live MIDI stream, adding control changes based on notes received. Briefly: use MDM by connecting a MIDI device, open preferences and set MIDI input...


Platforms: *nix

scnANNlib is a Sentinel Chicken Networks Artificial Neural Network Library. Documentation on what is what can be found in README.files. Currently, the API specification and documentation can only be found in the source of the header files (in lib/), but this will be improved in later releases....


Platforms: *nix

SPICE-MLP (the old name is SpiceNeuro or Neural Network Example - NNE) is a small application of Three-Layer Neural Network (NN) with multi-inputs and outputs, written for students who wanted to learn and develop their own NN applications. The purpose of this program is to get you started...


Platforms: Windows, Windows Vista, 7