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Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.
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.
The PORTIONS (PORTlets actIONS) framework allows you to develope JSR-168 portlets as if you were developing J2EE Web applications using Struts. It has been tested in Pluto 1.0.1, Jetspeed 2.0, JBoss Portal 2.4.1-GA and Vignette Application Portal 7.2
This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.
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