Search Results for "genetic algorithm in matlab" - Page 5
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Showing 314 open source projects for "genetic algorithm in matlab"
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Matlab Algorithm To C or C++
Matlab Mupad algo demos to C and C++
A demo with Matlab Mupad with an Options Call and Put algos converted to various C and C++ projects. You could also use Simulink for even FPGA deployment via HDL for ultra lowest high frequency trading -
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LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar... -
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SubPatCNV
Approximate association pattern mining algorithm for CNVs.
... samples?". SubPatCNV is the implementation of a variation of approximate association pattern mining algorithm under a spatial constraint on the positional CNV probe features. The implementation scales to high-density array data with hundreds of thousands features. -
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Evolutionary Nursery
A simple genetic algorithm for numerical optimization
Evolutionary nursery is a result for my passion for developing genetic algorithms. I implemented this simple GA in 2008. This is especially intended for numerical optimization problems. -
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Grammatical Optimization
A java based framework for grammatical evolution.
This project is a result for my curiosity for how grammatical evolution (GE) works. Eventually, I made this wrapper for GE that should work with any numerical optimization algorithm. So the idea behind GE is that it takes production rules for computer programs using a context free grammar in Backus Naur form. The production rules can be used to evolve computer programs by running an algorithm such as a genetic algorithm or a particle swarm optimizer in the background. -
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VisionLoc
Vision algorithm for the localization of robots in 2D
Vision algorithm for the localization of robots in 2D. The library can be called from a C, C++ or Matlab code. -
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SIMBUCA (before called Simonion) is a simulation package that simulates the motion of charged particles under the influence of Electric and/or Magnetic fields. What makes Simbuca unique is that you can choose to calculate the Coulomb interaction between ions on a Graphics cards which is much faster than calculating this on the conventional CPU (reducing the simulation time from years to days). Therefore Simbuca has been applied in various projects which required to understand the...
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FamSeq
Variant calling on the basis of pedigree information
... implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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PrivLocal/PrivGene
Differentially Private Model Fitting Using Genetic Algorithms
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SimpleFB_GA
a simple genetic algorithm written in FreeBasic
a FreeBasic-written Genetic Algorithm code is here deployed -
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HfT GA RCPSP
Genetic Algorithm for the RCPSP
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NEAT Visualizer SFML
A NEAT Implementation and Visualization System
Evolves neural networks using the Neuro-Evolution of Augmenting Topologies (NEAT) technique. A separate visualization system uses another genetic algorithm to evolve images of the otherwise dimensionless networks so their structure can be observed. -
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VariantMaster
Extract causative variants for monogenic and sporadic genetic diseases
There is a fast growing interest in clinical genetics to the utilization of High Throughput Sequencing data for accurate diagnosis of monogenic diseases. To improve the identification of the variants from HTS, we developed VariantMaster, an original program that accurately and efficiently extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM... -
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Bin Packing with Genectic Algorithm
Bin Packing problem solved using Genectic Algorithm
This project contains a solution for a Bin Packing problem solved using Genectic Algorithms. The code in the project was created as a solution for a problem in a combinatorial optimization class at the Univeridade Federal do Rio Grande do Sul (UFRGS - Brasil) in 2007. -
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MIT SPHERES Simulation (Release)
MIT's spacecraft simulator for control algorithm development
The SPHERES simulation is designed to support most software-related aspects of single- and multi-satellite SPHERES operations. The simulation code base consists of simulated versions of most of the SPHERES core flight code and additional code that simulates dynamics, communications, and other environmental interaction. The simulation is particularly valuable during the early stages of algorithm development and implementation as an aid in accelerating the learning curve for any Guest... -
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niGA
Heterogenous Multiprocessor Scheduling Using Genetic Algorithms
Implementation of task scheduling using Genetics algorithm for heterogeneous parallel programming -
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OBSOLETE s-ga
genetic algorithm
Obsolete. Moved to the new Project 'sgena' -
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
... fitting: 1. Full Factorial Design 2. Simple Random Sampling 3. Latin Hypercube Sampling 4. 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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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... -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. In addition to the standard Python libraries, PyGAO uses numpy. -
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Model Based Test Generator
Model Based Test Generator from UML
The purpose of this project is creating test cases from uml statemachine and Class diagram with OCL constraint. We use forward search strategy to creating abstract test cases and using genetic algorithm for creating test data. -
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NNBrain
A free, open source collection of neural network based AI agents.
NNBrain is a free and open source collection of artificial intelligence agents. These agents have applications in video games, research, business, and more. The included agents function in both discrete and continuous action and state spaces. -
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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...
