Freeware Downloads for "Genetic Simulations"

SFS_CODE (Selection on Finite Sites under COmplex Demographic Events) performs forward population genetic simulations under a general Wright-Fisher model with arbitrary demographic, selective, and mutational effects..

Simple Genetic Algorithm is an API for programming simulations that implement a genetic algorithm. A genetic algorithm is a search technique used in artficial intelligence to find approximate solutions to optimization and search problems.
Simple Genetic Algorithm API License - Academic Free License (AFL).

  • Platform: WinOther
  • Publisher: Simplega
  • Date:
  • JAS
  • License: Freeware
  • Rating

JAS is a java library for creating agent based simulations. It features a discrete-event time engine, APIs for network simulation design, powerful yet easy-to-use implementations of Genetic Algorithms and Neural Networks..

NaruGo is game AI project. Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem..

The Genetic Algorithm Utility Library (or, GAUL for short) is a flexible programming library designed to aid in the development of applications that use genetic, or evolutionary, algorithms. It provides data structures and functions for handling and manipulation of the data required for serial and parallel evolutionary algorithms. Additional stochastic algorithms are provided for comparison to the genetic algorithms. Much of the functionality is also available through a simple S-Lang interface. Features: - Darwinian, Lamarckian or Baldwinian evolutionary schemes.

  • Platform: C and C plus plus, Scripts
  • Publisher: Stewart Adcock
  • Date: 22-05-2013
  • Size: 553 KB

PID controller has been extensively used in the industrial world. But in this controller it is difficult to tune the PID gains. We apply the genetic algorithm(GA) to tune the PID gains. The GA is agorithm using the biotic; gene the biotic; genetics..

This set of files show some of the principles of Monte Carlo simulations, applied in the financial industry. this is the content of the web seminar called "Simulations de Monte Carlo en MATLAB". The slides are in French and a copy in English is also available You will find here : * how to code your own monte carlo simulation, for option pricing * a comparison of some of the Variance Reduction Technics * Benfeits of using MATLAB for MonteCarlo simulation.

  • Platform: Matlab, Scripts
  • Publisher: Vincent Leclercq
  • Date: 17-03-2013
  • Size: 399 KB

We use the genetic algorithm (gatool) to determine the four parameters of the implicit Forst-Kalkwarf-Thodos Model. Predictions are in perfect agreement with data of vapour pressure of iodobenzene versus temperature for a temperature range from 380.15 K to 580.15 K..

  • Platform: Matlab, Scripts
  • Publisher: Housam Binous
  • Date: 07-01-2013
  • Size: 10 KB

genetic algorithm (or GA) is a search technique used in computing to find true or approximate solutions to optimization and search problems for function of 2 variable.

Files used in the Webinar "Developing a Financial Market Index Tracker using MATLAB OOP and Genetic Algorithms" The zip file contains the data and files used to develop an application to track a market index using Genetic algorithm. The initial algorithm is then wrapped up in MATLAB OOP to create an applcation, which can then be tested against the data. Also included aresimple demo files of both genetic algorithms and MATLAB OOP..

  • Platform: Matlab, Scripts
  • Publisher: Mark Hoyle
  • Date: 19-03-2013
  • Size: 2099 KB

Optimisation for 4 variables using Genetic technique. Was designed to optimise surface impedance measurements.

  • Platform: Matlab, Scripts
  • Publisher: David Ireland
  • Date: 07-04-2013
  • Size: 10 KB

Set of simulations you can run on, and JDClosed **Calls JDEuropean.m & JDClosed.m.

  • Platform: Matlab, Scripts
  • Publisher: Nils Delava
  • Date: 26-05-2013
  • Size: 10 KB

Multivariate normal simulations where sample mean and covariances match the respective population moments, refer to A. Meucci (2009), "Simulations with Exact Means and Covariances", Latest version of article and code available at http://symmys.com/node/162.

  • Platform: Matlab, Scripts
  • Publisher: Attilio Meucci
  • Date: 21-04-2013
  • Size: 10 KB

Genetic Algorithms Library, or was specially developed as an accessible and useful API that is intended to help developers use genetic algorithms in their own Java applications.

The Genetic Algorithms Library can now be used to further improve your development process.



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Java Genetic Algorithm Library is a handy, Java based object oriented library of an Genetic Algorithm. Clear separation of the several concepts of the algorithm, like Gene, Chromosome, Genotype, Phenotype, Population and FitnessFunction.

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Open Genetic Algorithm Toolbox was developed as an accessible MATLAB tool that allows you to run a Genetic Algorithms on any problem you want to model.

Genetic Algorithms are search heuristics developed to find solutions to any problem through bio-inspired heuristics.

Now, you can use this accessible toolbox to quickly find solutions to your problems.


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A.I. Solver Studio is a unique pattern recognition application that deals with finding optimal solutions to classification problems and uses several powerful and proven artificial intelligence techniques including neural networks, genetic programming and genetic algorithms. No special knowledge is required of users as A.I. Solver Studio manages all the complexities of the problem solving internally. This leaves users free to concentrate on formulating their problems of interest.Typically, all that is required of users is that they formulate their problems by creating training data and test data.

A general purpose GA toolkit implemented in Java, designed for experimenting with genetic algorithms and handling diverse optimization problems..

  • Platform: JavaScript, Scripts
  • Publisher: Ariel Dolan
  • Date: 16-03-2011

This program, BayeScan aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. BayeScan is based on the multinomial-Dirichlet model. One of the simplest possible scenarios covered consists of an island model in which subpopulation allele frequencies are correlated through a common migrant gene pool from which they differ in varying degrees. The difference in allele frequency between this common gene pool and each subpopulation is measured by a subpopulation specific FST coefficient.

  • Platform: WinOther
  • Publisher: Matthieu Foll
  • Date: 22-11-2012
  • Size: 3379 KB

GUI for distribution of OMNeT++ simulations on different computers. This software includes server and simulation management and uses Java SWT and Web Services..

Genetic Simulations: Freeware | All

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