Genetic Research

This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported. Platforms: Windows, Mac, Linux

This easy to run and change program for developers, it contains several evolutionary based strategies allowing you try among some function samples Platforms: Windows, Mac, Linux

ResearchMaster is a tool that you can trust to help with organization, multitasking, and research. ResearchMaster provides a place to capture your fleeting thoughts and ideas, and it allows you to hit-the-ground-running on projects. Platforms: Windows, Mac, Linux

Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm. Platforms: Windows, Mac, Linux

Trilobots is an arcade-style shooter that evolves the abilities and programming of the enemies using a genetic algorithm. The end goal is to make the evolution transparent, allowing users to learn how genetic algorithms work while having fun. Platforms: Windows, Mac, Linux

VKAS uses genetic programming methods to find out the relationship among a set of independent and dependent variable. It is a problem solver software which uses evolutionary computing methods. Platforms: Windows, Mac, Linux

M-files accompanying the " Genetic Algorithms & New Optimization Methods in MATLAB " webinar.These files provide what you need to run the two demos: Optimization of non-smooth objective function, and Optimization of a random stochastic objective function.To run the first demo run the file... Platforms: Matlab

The Particle Swarm Optimization Research Toolbox was written to assist with thesis research combating the premature convergence problem of particle swarm optimization (PSO). The control panel offers ample flexibility to accommodate various research directions. After specifying your intentions,... Platforms: Matlab

This zip file contains the Presentation (PDF) and M-files that were demonstrated in the MathWorks Webinar: Using Genetic Algorithms in Financial Applications delivered on Dec 11 2007.The purpose of the webinar was to highlight how Genetic Algorithms may be used to supplement portfolio... Platforms: Matlab

This code proposes genetic algorithm (GA) to optimize the point-to-point trajectory planning for a 3-link (redundant) robotarm. The objective function for the proposed GA is to minimizing traveling time and space, while not exceeding a maximumpre-defined torque, without collision with any... Platforms: Matlab

SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language. Without bells and whistles, it faithfully implements the specification for a Simple GA given on pgs 10, 11 of M. Mitchell's GA book. See comments in code for details.This script has played a crucial... Platforms: Matlab

We use the genetic algorithm (gatool) to determine the three parameters of the simple Antoine equation and the six parameters of the Modified Antoine Model. Predictions are in perfect agreement with experimental data of vapor pressure of ethanol versus temperature for a temperature range from... Platforms: Matlab

The script allows to easily fit predefined complex analytical laws exploiting the potentiality of Genetic Algorithms.The script receives as input the handle to the analytic laws to be fitted to data. Such law may depend on multiple variables and several parameters. This optimization approach may... Platforms: Matlab

http://simulations.narod.ru/See research.docx for explanations of method used.The task is to find algorithm where you can get sound from microphone of piano and the algorithm must recognize it and print it in textbox.Reached result:1 note: 93% of right answers2 notes simultaneously : 61% of right... Platforms: Matlab

These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta. Formulae were adapted from Sokal and Rohlf's 1995 Biometry, and test files from the book are given as reference. Platforms: Matlab

Extended compact genetic algorithm (ECGA) is an algorithm that can solve hard problemsin the binary domain. ECGA is reliable and accurate because of the capability ofdetecting building blocks, but certain difficulties are encountered when we directly applyECGA to problems in the integer domain.... Platforms: Matlab

This particular hybrid genetic optimizer is referenced from: J Hu "Radio Frequency Front-End Measurement and Modeling," Ph.D. dissertation, North Carolina State University, Raleigh NC, 2011.It's used in fitting a RF power amplifier model to measured data and extracting the model parameters. Platforms: Matlab

N-queen generalized genetic algorithm. Parameters can be changed and tested.It has very basic but effective functions of selection,crossover and mutation.Queens are randomly positioned in the beginning.I have written it for n-queens.It gives a good amount of solutions for queens > 8.Also you can... Platforms: Matlab

Use the mixed-integer genetic algorithm to solve an engineering design problem.Designs often require that components come from a list of available sizes. In this example, we show how the Genetic Algorithm can be used to find values for the Resistors and Thermistors in a circuit that meet our... Platforms: Matlab

This script executes some basic calculations from the following article.Leonard AC, Franson SE, Hertzberg VS, Smith MK & Toth GP (1999) Hypothesis testing with the similarity index. Molecular Ecology 8: 2105-2114.Please consult this article for any conceptual or mathematical details.The script... Platforms: Matlab