Showing 163 open source projects for "genetic algorithm java"

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  • 1
    Modified NCBI Toolkit for Windows, added contextual BLAST algorithm.
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  • 2
    JGAL is a Java Genetic Algorithms Library.
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  • 3
    This Project implements the mergesort algorithm in a MPICH2 (parallel programming -) environment.
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  • 4
    A concise example of the classical genetic algorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
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  • 5
    A framework for utilising the Genetic Algorithm in the domain of Game Theory
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  • 6
    The algorithm used by this MasterMind applet is very simple. Yet it is also very fast and it uses relatively few guesses.
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  • 7
    Project Tokaf is an general implementation of top-k algorithm. It provides interfaces for all modules that are needed. It also features user preferences module, for computing new preferences and manipulating existing ones.
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  • 8
    KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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  • 9
    The main goal of OWLVE is to visualize graphically any OWL–lite file. Using powerful RCP and GEF technologies will improve the quality of graphics and diagrams.This project includes an algorithm for similarity calculus between two OWL files.
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  • 10
    A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
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  • 11
    OAP Lite is Optimized Algorithms Platform Lite, which simplifies the process of solving some optimization problems by Genetic Algorithms. It is a highly configurable, efficient tool for user to get the optimum result without programming.
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  • 12
    M+ Compiler/Interpreter is a interpreter library written in Java that delivers the possibility to extend any Java application with simple scripts. Besides the usage of native datatypes and operations you can instantiate and call native Java objects.
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  • 13
    Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.
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  • 14
    This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
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  • 15
    EvoTrader is a stock picking platform that utilizes genetic programming to evolve rules for generating stock trading signals.
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  • 16
    musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
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  • 17
    Aggressive Rectangle Truncation (ART) with Location Verfication Mechanism is a localization algorithm in wireless sensor networks written in nesC.
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  • 18
    StrMatch is a simple java program, created for educational purposes, that allows user to test a great part of string matching algorithms. An intuitive user interface shows each algorithm step accurately...
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  • 19
    Agenda desenvolvida em Java, utilizando banco PostGreSQL. Itens: Cadastro de Contatos Cadastro de Tarefas
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  • 20
    Genetic Algorithm based software to resolve the Traveling Salesman Problem (Problema del Commesso Viaggiatore).
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  • 21
    This project aims to provide developers a convenient library about graph theory algorithm and some basic data structures. It will be developed in Java via Eclipse IDE, supporting both win32 and linux systems, and published as jar files.
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  • 22
    This project's goal is to implement Artificial Inteligence algorithms and make them available for any platform but especially for mobile devices. The main objective is to allow the community to develop better and more inteligent mobile games.
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  • 23
    Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
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  • 24
    MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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  • 25
    Genetic Algorithm implementation.
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