Search Results for "genetic algorithm java" - Page 5
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Showing 138 open source projects for "genetic algorithm java"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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OW.NET -- 1-Wire API port from Java (and J#) to C#. Use the Dallas 1-Wire and iButton chips with standard C# using a serial adapter (also CF.net) or the TMEX drivers on the Windows platform. No J# distribution installation required.
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The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
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JNSGA2 is a Java library with an implementation of the multi-objective genetic algorithm NSGA-II published by Deb et al.
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Dominate AI Search ResultsAthenaHQ is a cutting-edge platform for Generative Engine Optimization (GEO), designed to help brands optimize their visibility and performance across AI-driven search platforms like ChatGPT, Google AI, and more.
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An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.
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A simulation environment for 2D robots to interact and perform tasks in. Meant to be educational and demonstrate emergent behaviors. No download necessary! See demos on project website!
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The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
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The simpliZia-program implements the simplex-algorithm and is designed to help students of Operations Research to understand and learn the algorithm. This is a german project, source and program are actually written in german.
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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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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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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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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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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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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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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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EvoTrader is a stock picking platform that utilizes genetic programming to evolve rules for generating stock trading signals.
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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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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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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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Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
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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.
