Search Results for "matlab genetic algorithm" - Page 4
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Showing 330 open source projects for "matlab genetic algorithm"
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Density-ratio based clustering
Discovering clusters with varying densities
This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying... -
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MicroGP
A multi-purpose extensible self-adaptive evolutionary algorithm
MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4 -
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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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tsp-problem-ga-aco-comparisson
Genetic Algorithm and Ant Colony to solve the TSP problem
This project compares the classical implementation of Genetic Algorithm and Ant Colony Optimization, to solve a TSP problem. It's possible to define the number of cities to visit , and also interactively create new cities to visit in a 2D spatial panel. A total distance is given for AG and ACO solution at end. -
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Sched-Resched
A C++ schedule generator based on Genetic Algorithm and Hill Climbing
Sched-Sched is a C++ schedule generator for software project staffing and rescheduling based on Genetic Algorithm (GA) and Hill Climbing (HC). It is implemented with GALib (http://lancet.mit.edu/ga/), an open-source toolkit of Genetic Algorithms in various platforms including Unix and Windows. The input and output files of the software are required as XML format. The input file includes tasks' and employees' information according to predefined file format. The generated output XML file... -
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theoEA_Code
genetic algorithm for optimizing planar optical antennas
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Sched-SPM
A C++ schedule generator based on Genetic Algorithm and Hill Climbing
Sched-SPM is a C++ schedule generator for software project staffing and rescheduling based on Genetic Algorithm (GA) and Hill Climbing (HC). This preliminary tool is mainly for academic purpose. It is implemented with GALib (http://lancet.mit.edu/ga/), an open-source toolkit of Genetic Algorithms in various platforms including Unix and Windows. The input and output files of the software are required as XML format. The input file includes tasks' and employees' information according... -
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... of the Riemannian Hessian (if a Newton method is used) in Matlab or C++. The package optimizes the function given a set of user-specified parameters, e.g., the domain manifold, algorithm, stopping criterion.
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swe2d
Matlab 2D Shallow Water Solver
This is a set of matlab codes to solve the depth-averaged shallow water equations following the method of Casulli (1990) in which the free-surface is solved with the theta method and momentum advection is computed with the Eulerian-Lagrangian method (ELM). The free-surface equation is computed with the conjugate-gradient algorithm. Casulli, V. (1990) Semi-implicit finite difference methods for the two-dimensional shallow water equations, J. Comp. Phys., 86 (1), 56-74. -
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
.... To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach. Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers. The classification performances achieved by the proposed method method on the chosen datasets are promising. -
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classify-20-NG-with-4-ML-Algo
Problem involves classifying 20000 messages into different 20 classes
.... Each of these algorithms has its peculiar data format; the specific format and how to reconstruct the entire dataset are illustrated in other sections below. Out of all the methods, SVM using the Libsvm [1] produced the most accurate and optimized result for its classification accuracy for the 20 classes. All the algorithm implementation was written Matlab. Download the code and Report here. -
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REDHORSE
Software suite for the analysis of haploid hybrids using NGS
The alignments to the genome from next-generation-sequencing (NGS) data cannot be directly used as input to the existing recombination detection (RD) algorithms that use multiple sequence alignments (MSA). We therefore designed a software suite called REDHORSE that takes genomic alignments as input, extracts meaningful markers and generates MSAs that are the inputs to existing RD algorithms. In addition, REDHORSE implements a custom RD algorithm that makes use of sequence information... -
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This software searches the potential energy surface of small to medium size atomic systems for global minima using quantum ab initio techniques. It performs bond rotations and molecule translations and rotations on a Linux cluster with MPI.
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Object detection is usually a software-based monitoring algorithm that will signal, for example in the surveillance camera to begin capturing the event when it detects motion. In object tracking, the object is located and the moving object is followed. One of the fundamental steps in many computer based vision systems for object tracking and motion detection is real-time segmentation of moving regions in the image sequences. Segmentation is done in order to detect the object accurately...
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GI-ICA
Matlab implementation of GI-ICA and PEGI
This is a matlab implementation of the GI-ICA algorithm for ICA in the presence of an additive Gaussian noise. The algorithm is discussed in the paper "Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis" by James Voss, Luis Rademacher, and Mikhail Belkin. -
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BiRW
Bi-random Walks for Phenome-Genome Association Prediction
The availability of ontologies and systematic documentations of phenotypes and their genetic associations has enabled large-scale network-based global analyses of the association between the complete collection of phenotypes (phenome) and genes. BiRW is a package designed for analysis and prediction of the phenome-genome associations. BiRW package contains a program for analysis of circular bigraphs (CBGs) and the bi-random walk (BiRW) algorithm to capture the CBG patterns in the networks... -
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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. -
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JAABA
The Janelia Automated Animal Behavior Annotator
... detectors that can then be used to automatically classify the behaviors of animals in large data sets with high throughput. JAABA combines an intuitive graphical user interface, a fast and powerful machine learning algorithm, and visualizations of the classifier into an interactive, usable system for creating automatic behavior detectors. Documentation is available at: http://jaaba.sourceforge.net/ -
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Constrained Ellipse Fitting
MATLAB Code for Constrained Ellipse Fitting with Center on a Line
The provided Matlab code allows for fitting an ellipse to given data points with the additional prior knowledge that the center of the ellipse is located on a given line. The usage of this constraint in a new global convergent one-dimensional search problem ("Tunneling") improves the fitting accuracy compared to other ellipse fitting methods. You can find more details on the theoretical background of the presented algorithm here: http://doi.org/10.1007/s10851-015-0584-x If you use the code... -
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ObjectDetector
Car Detection,Face Detectiom,Object Detection
Machine learning: This project is used for training new object like Car,Motor Cycle and so on and we use this model(xml file) for detecting in images.In this project we use viola jones algorithm. -
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mAPV
modified Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model -
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cusAPV
customized Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a customized Asymmetric Pseudo-Voigt model -
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Java CoreWars Evolver
A Java based, pMars compatible, CoreWars simulator with GA
A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 8 is needed. See [Wiki:Tutorial] -
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Glycosylation Microviewer
An application create, simulate and adjust N-linked glycosylation.
Glycosylation Microviewer is an application that create N-linked glycosylation raction network. The model used in the application is based on two significant papers: 1.1997 Pablo Umana, James E.Bailey A Mathematical Model of N-linked Glycoform Biosynthesis. 2.2005 Frederick J.Krambeck, Michael J.Betenbaugh A Mathematical Model of N-linked Glycosylation. The application allow to simulate the network in dynamic form with various ODE solvers(Euler, Runge-Kutta etc). Genetic Algorithm... -
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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...
