Search Results for "virtual-machine"

The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.

...The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. To use the genetic algorithm engine to search for a different problem's solution, one needs to program a fitness function, the project settings, and a few virtual functions.

EASEA (EAsy Specification of Evolutionary Algorithms: pronounce "easy") is a high-level language dedicated to the specification of evolutionary algorithms. EASEA up to version 0.7 compiles .ez specification files into C++ or JAVA object files.

Flexible job shop scheduling problem (FJSP) is very important in many fields such as production management, resource allocation and combinatorial optimization. In the real manufacturing systems, each operation could be processed on more than one machine and each machine can also process several operations. This feature is known as flexibility. You can define your problem in this software and get an optimal solution as a Gantt Chart. This software is based on my M.Sc. thesis of Shahed university (Tehran, Iran).

A GPU-based efficient data parallel formulation of the k-Nearest Neighbor (kNN) search problem which is a popular method for classifying objects in several fields of research, such as- pattern recognition, machine learning, bioinformatics etc.

RobGP is a genetic programming system written from the ground up in C++. It's primary goals are efficiency, ease of use, and extensibility. It's distinguishing feature is that it has a modified version of Koza's architecture altering operations.

The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover

Todbot is an AI addon to the gamestool virtual machine. The aim is to create an evolving neural network topology that should be capable of creating the optimal topology and network weighting to solve any problem given it.

A tool that helps develope the course of cognitive thought processes through software. This tool will look at the raw hex code of any input. It establishes pattern recognition over a mesured time incrament that in itself is at a different pace.

Geneur is an Open Source scheduler for GRID. It is based on variation of genetic algorithms. Geneur uses backfill scheduling algorithm to create first genetic population.

Este projeto objetiva a criação de um Toolbox para utilização de algoritmos de Computação Bioinspirada. O Toobox oferece uma vasta coleção de algoritmos de ferramentas para o projeto de Algoritmos Genéticos e Redes Neurais.

Multiclass machine learning

This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.

Animants are virtual ants. Their name comes from the combination of "ants" and "animats", an animat being "a sofware approximation of a living creature". Animants aim to simulate the behaviour of living animals.

A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks.

Takthons provides container and manipulation services for evolved machine language routines. This allows the calling application to concentrate on the UI, the fitness evaluation and the genetic operations rather than the machine language details.

A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.