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GA: Generic genetic algorithms base implementation

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Picture of Rafael Pinto
Name: Rafael Pinto <e-mail contact>
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Country: Brazil Brazil - PHP jobs in Brazil
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This class implements base methods to apply genetic algorithms to arbitrary subjects.

Its functions can be call instantiating a class object or called static methods.

The class can perform several types of generic algorithm operations like crossover, mutation, selection and death over populations of any objects of the same class.

It can be used as a base implementation of genetic algorithms to solve many types of problems on which the best solution may be found through natural selection.

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Name: GA
Base name: ga
Description: Generic genetic algorithms base implementation
Version: -
PHP version: -
License: GNU General Public License (GPL)
All time users: 3360 users
All time rank: 946
Week users: 10 users
Week rank: 136 Up
 
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  Groups  
Group folder image Algorithms Numerical and statistical algorithms View top rated classes
Group folder image Artificial intelligence Automation of tasks using human-like intelligence View top rated classes


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PHP Programming Innovation award winner
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Genetic Algorithms are computing algorithms used to find approximate solutions to optimization problems. These problems consist in determining sequences of data that may provide better results depending on the order of the data elements.

The genetic algorithms are inspired in the evolutionary biology theories that determine that on each generation the individuals tend to evolve and address better the problems that challenge their survival.

Evolution happens after performing slight mutations to the chromosome sequence of the individuals of the current generation. The best fit individuals will survive and become the origin of the next generation.

In computing genetic algorithms can be used to optimize solutions for problems like job scheduling, artificial intelligence for computer operated game characters, compact file storage, etc..

This class can be used as a framework to implement PHP applications that can benefit of the use of genetic algorithms.

Manuel Lemos

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All time: Sufficient (65.0%) Sufficient (75.0%) - Sufficient (70.0%) - - Not sure (47.0%) 1767
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  Related links  
Link Description
Genetic Algorithms Genetic Algorithms
Introduction to Genetic Algorithms Introduction to Genetic Algorithms
The Genetic Algorithms Archive The Genetic Algorithms Archive

  Files folder image Files  
File Role Description
Plain text file ga.php Class GA Class
Accessible without login Plain text file gaExample1.php Example GA Example 1
Accessible without login Plain text file gaExample2.php Example GA Example 2

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