Search Results for "parallel genetic algorithm" - Page 12

Web Textual eXtraction Tools C++ Parallel web crawler, noun phrase idenification, Multi-lingual Part of Speech Tagging, Tarjan's Algorithm, Co-RelationShip Mappings...

A Gtkmm Othello-like game that supports one player ( with both random move selection and genetic algorithm based selection), two players, and network play.

UbWator II is an artificial life simulation inspired by A. K. Dewdney, in his "Computer Recreations" article in the December, 1984 issue of Scientific American. Moreover we are going to add some genetic algorithm. We start from an existing Delphi prog

This project is the work of four students in Bioinformatics and Modeling at Insa de Lyon, a French engineering school. Through the use of a genetic algorithm we will try to show the stablishment of speciation resulting from coevolution of automats

TA scheduler based on a genetic algorithm to make the tedious task of scheduling TA's more efficient.

The Athlete is a virtual robot living in the ODE (Open Dynamics Engine)world. An evolution algorithm is implemented based on the DR-EA-M to optimize its performances. This involves a Genetic algorithm, network of neurons and morphology. All is in java.

GD is AI - ALife becoming true. It's a genetic engine server, capable to run any kind of genetic algorithm. It has TCP architetcure, working with software clients and uman interaction. It has plugin capabilities and comes with a working Function Finder

MAGMA: Multiobjective Analyzer for Genetic Marker Acquisition A genetic algorithm for generating SNP tiling paths from a large SNP database based on the competing objectives of cost (number of SNPs) and coverage (haplotype blocks): Hubley R., Zitzler

PPAT, or Parallel Path following Algorithm using Triangles, is a reliable parallel tool to trace the level curves of any continuous, not necessarily smooth, function f(z): C → R.

Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.

ga2 is a simple C++ library providing the necessary base classes to implement a genetic algorithm in C++. It is based loosely on Goldberg's canonical GA, but with many modifications, improvements and additional features. Essentially feature-complete, and

Domigene is a genetic algorithm API attempting to incorporate dominant and recessive genes. Supports modular evolution types, genetic programs, definable instruction sets, variation in population, chromosomes, mortality, mutation, fitness functions.

A program that will grow realistic trees using the genetic algorithm.

Distributed Genetic Algorithm framework (with projects). Uses java.rmi for networking.

A Genetic Algorithm Training System in Python. Gatspy provides the framework, the user provides the error (fitness) function. Gatspy will evolve a solution that attempts to minimize the error.

The goal of the Rats and Mazes project is to build a simple genetic algorithm to find general solutions to random non-cyclic single path mazes. I believe that the solutions will tend towards either the right/left-hand rule.

This is a very simple implementation of the genetic algorithm framework presented by John Holland, based on Goldberg book Genetic Algorithms in Search, Optimization and Machine Learning.

R based genetic algorithm for optimization, variable selection and other machine learning and statistical analysis approaches.

aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.

This project aims at using the Artificial Intelligence (AI) algorithm called the Genetic algorithm to solve the problem of placement in the FPGA circuits.

Aim behind implementing these algorithms 1. Study Sub-cube Matrix Decomposition (SMD) Implementation of SMD using LU factorization algorithm 2. Study how to unify parallel implementations of the same algorithm in decomposition in independent way. Implementation of LU factorization algorithm based on Sub-cube Matrix Decomposition, Row decomposition and Column decomposition. 3. Study how to optimize naïve parallel programs maintaining the decomposition independence. Implementation of LU...

Application to test a GA solution for the Knapsack problem, it will compare Genetic Algorithm solution of the Knapsack problem to greedy algorithm.

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

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.