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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 optimization problems. The Genetic Algorithm contains custom evolution algorithms that were built specifically for this webinar. They allow the user...



This code is a demo of using Genetic Algorithms (GA) to solve a simple constrained multi-objective optimization (MOO) problem.

The objective is to find the pareto front of the MOO problem defined as follows:
Maximize:
f1(X)...



This code identifies an ARX model of a system using Genetic Algorithms method in a GUI interfcae and compares the identified model with the model generated using the Least Error method.

The real system O/P, GA model generated O/p and...



This function implements a method of using genetic algorithms to optimise the form of a polynomial, i.e. reducing the number of terms required in comparison to a least-squares fit using all possible terms, as described in the following paper:



Classroom allocation using Genetic Algorithms and restricted mutation. Developed by AIGroup: Pablo Cababie, Facundo Cancelo, Alvaro Zweig y Gabriel Barrera



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...



The function generates sequency(Walsh) ordered Hadamard matrix useful for image processing, signal processing, genetic algorithms etc.



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...



An optimized java library for genetic algorithms. The library is designed to be fast and memory light, but still very easy to use.



This API is intended to help developers use genetic algorithms in their own java applications. GeneticLibrary.zip contains the netbeans project of the API itself. GeneticTrial.zip contains another netbeans project which is an example explaining...



JGAL is a Java Genetic Algorithms Library.



This project aims to create an open source genetic algorithms (GA) library for the IBM Cell BE processor. A well-documented implementation of GAs is provided, along with a number of sample fitness functions illustrating how to use the GA library.



simple but powerful, open source, c++ genetic algorithms class library for optimization and search purposes.



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.



Generic class for genetic algorithms, making it possible to evolve any class.



A Qt IDE for building and running Genetic Algorithms using the GAlib library. Started as a conclusion work for graduation in Computer Science in UDESC-CCT .



The function implement the 1D Walash Transform which can be used in signal processing,pattern recognition and Genetic algorithms. The Formula of 1D Walsh Transform is defined as :

N-1 q-1
---- --
1 | |...



The function implement the 1D Walash Transform which can be used in signal processing,pattern recognition and Genetic algorithms. The Formula of 1D Walsh Transform is defined in mfile



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



Genetic algorithms, Machine learning, and Neural network. Artificial intelligence for ruby, working and ready to use in you app.