Search Results for "genetic algorithm cloudsim" - Page 7
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Showing 161 open source projects for "genetic algorithm cloudsim"
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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
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Domigene is a genetic algorithm API attempting to incorporate dominant and recessive genes. Supports modular evolution types, genetic programs, definable instruction sets, variation in population, chromosomes, mortality, mutation, fitness functions.
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A Genetic Algorithm Training System in Python. Gatspy provides the framework, the user provides the error (fitness) function. Gatspy will evolve a solution that attempts to minimize the error.
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aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
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R based genetic algorithm for optimization, variable selection and other machine learning and statistical analysis approaches.
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A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
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GAZES - Genetic Algorithm Zombie Eradication Simulation Grid-based simulator for zombie scenario. The units will use genetic algorithm to determine their actions on a cycle by cycle basis. This is a school project, so is likely on hiatus for summer.
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cosmos
Algorithms that run our universe | Your personal library of every algo
Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
