Search Results for "genetic algorithm simulation toolbox"
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Showing 30 open source projects for "genetic algorithm simulation toolbox"
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Genetic algorithm for EOM
A python GA code for EOM in SAXS/WAXS
Because GAjoe of ATSAS cannot deal with WAXS range, and no parameters can be modified. I made a code by myself to use GA for finding best EOM for SAXS/WAXS. The project need ATSAS crysol and a folder with multiple pdb files to use. -
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NKTgLaw
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core implementation, REST/gRPC API, and 150+ client wrappers -
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GeneticSharp
GeneticSharp is a fast, extensible, multi-platform and multithreading
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). A Blazor... -
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NaveGo
NaveGo: an open source MATLAB/GNU Octave toolbox for processing integr
NaveGo is an open source MATLAB/GNU Octave toolbox designed for processing integrated navigation systems, simulating inertial sensors and GNSS receivers, and profiling inertial sensors using methods like Allan variance—providing a community-driven simulation framework for navigation system design and analysis. I am reaching out to share an important update regarding the NaveGo project. Due to a shift in both my professional career and personal interests away from navigation systems, I have... -
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GenCodeGenerator
C++ class to generate biologically plausible genetic codes
The "GeneticCode" C++ class is designed to generate versions of the genetic code subject to the requirements of the three major models of the genetic code origin and evolution (about these models see, e.g., Koonin & Novozhilov, 2009, IUBMB Life). This class was written specifically to perform statistical test for the paper Makukov & shCherbak (2017), but it might be used for a wider class of studies related to the genetic code. By default, the class "GeneticCode" generates... -
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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... -
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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. User friendly GAMETES software... -
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ESTReMo
An evolutionary simulator of transcription regulatory networks
ESTReMo is a genetic algorithm-based simulator to explore the evolution of transcription factors and their binding motifs on realistic genomic backgrounds. -
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Evochumps
Evolving recursive artificial neural networks in a simulation.
Evochups allows you to create a simple simulation environment where individuals called "chumps" display behavior according to their simulated brains. Each Chump has a recursive neural network which takes input from thier environment and controls the chump's behavior. It has a built-in evolutionary algorith to let the brains evolve conditoned to selective pressure. The program's interface allows you to manipulate all kinds of parameters of both the simulation, the genetic algorithm, and each particular RNN in real time. -
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
...Quasi-Newton Method 5. Simulated Annealing 6. Genetic Algorithm 7. Approximate Bayesian Computation b. Sensitivity Analysis: 1. Local SA 2. Morris Screening 3. DoE 4. Partial (Rank) Correlation Coefficient 5. Standardised (Rank) Regression Coefficient 6. Sobol' 7. eFAST 8. FANOVA Decomposition Have also a look on our other projects: http://www.uni-goettingen.de/de/315075.html -
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Reactor Breeder
A Genetic Algorithm for Reactors in StarMade
This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors. -
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Open Genetic Algorithm Toolbox
This is a MATLAB toolbox to run a GA on any problem you want to model.
This is a toolbox to run a GA on any problem you want to model. You can use one of the sample problems as reference to model your own problem with a few simple functions. You can collaborate by defining new example problems or new functions for GA, such as scaling, selection or adaptation methods. In that case, you should then include your credits in the file, upload it to matlab central and contact the author. Suggestions are also welcome but naturally I won't be able to attend... -
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Bouc-Wen-Baber-Noori model of hysteresis
Compute parameters of the Bouc-Wen-Baber-Noori model of hysteresis
...Deb allowed me to use and post this toolbox. For further information about the toolbox read the documentation and the following papers: - Kalyanmoy Deb, Sameer Agrawal, Amrit Pratap, T Meyarivan. "A Fast and Elitist multi-objective Genetic Algorithm: NSGA-II". Journal IEEE Transactions on Evolutionary Computation (IEEE-TEC). 2002. Vol. 6. No. 2. pp. 182-197. - Gilberto A. -
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Java Evolutionary Computation Library
As of 2012-12-18, this project may now be found at Google Code.
As of 2012-12-18, this project may now be found at http://http://code.google.com/p/paba JECO is a Evolutionary Computation Library deveoloped in Java. It includes a variety of evolutionary optimization techniques such as genetic algorithm, genetic programming, evolutionary mapping methods, particle swarm optimization, ant colonies, etc. -
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PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.
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A genetic algorithm in Python for evolving programs that write a given string to an allocated dataspace, using a made-up machine language with only 7 instructions and flow reversal.
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This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
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Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.
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This easy to run and change program for developers, it contains several evolutionary based strategies allowing you try among some function samples
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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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Evolve is a simulation written in java that uses the Genetic Algorithm to evolve intelligent agents acting in a rich environment.
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A 2D rigid physics simulator and set of genetic algorithm tools. Evolve cute little walking creatures.
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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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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
