Showing 5 open source projects for "genetic algorithm fortran simple"

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  • 1
    Opt4J

    Opt4J

    Modular Java framework for meta-heuristic optimization

    Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary...
    Downloads: 1 This Week
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  • 2

    GeneticAlgorithms

    Framework for using the Genetic Algorithms optimization heuristic.

    GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later.
    Downloads: 3 This Week
    Last Update:
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  • 3

    gametes

    Generate complex SNP models and heterogeneous datasets

    Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) is an algorithm for the generation of complex single nucleotide polymorphism (SNP) models for simulated association studies. GAMETES is designed to generate epistatic models which we refer to as pure and strict, that constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model.
    Downloads: 3 This Week
    Last Update:
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  • 4
    Shape is a molecular conformation prediction program. It uses a genetic algorithm to efficiently search the conformational space of a biomolecule and then clusters the results. It is very simple to use.
    Downloads: 0 This Week
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  • 5
    Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
    Downloads: 0 This Week
    Last Update:
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