Search Results for "matlab genetic algorithm"
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Showing 335 open source projects for "matlab genetic algorithm"
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. ... -
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PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
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LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. -
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
...Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our aim is to provide a wide range of easy-to-use algorithms for the tomographic community "off the shelf". We would like to build a stronger bridge between algorithm developers and imaging researchers/clinicians by encouraging and supporting contributions from both sides to TIGRE. -
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The Operator Splitting QP Solver
The Operator Splitting QP Solver
OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust. -
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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pyeqsp
Python port of the eq_sphere_partitions Matlab toolbox
PyEQSP is a Python library that implements the Recursive Zonal Equal Area (EQ) Sphere Partitioning algorithm, originally developed as a Matlab toolbox by Paul Leopardi. For an overview of the features of PyEQSP, see README.md -
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VOP post-processing
Post-processing algorithms for SAR compression
***Please note that a much improved Version can be found on Github:*** https://github.com/sOrzada/VOP_Compression Here we introduce to algorithms for post-processing of VOP sets. Algorithm 1 reduces the Overestimation for a given set of VOPs. Especially useful to reduce the overestimation in VOP sets calculated with the compression algorithms by Lee et al. and Orzada et al. Algorithm 2 tests a given set of VOPs for redundancy. It can be used to reduce the number of VOPs in a... -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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GRAMPC
A gradient-based augmented Lagrangian framework for embedded NMPC
GRAMPC is a nonlinear MPC framework that is suitable for dynamical systems with sampling times in the (sub)millisecond range and that allows for an efficient implementation on embedded hardware. The algorithm is based on an augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. GRAMPC is implemented in plain C with an additional interface to C++ and MATLAB/Simulink. The basic structure and usage of GRAMPC are described in the documentation that comes along with the source files. More details about the algorithm and its performance can be found in the corresponding article published in Optimization and Engeneering. ... -
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High-performance package for SemiDefinite Programs The software SDPA (SemiDefinite Programming Algorithm) is one of the most efficient and stable software packages for solving SDPs based on the primal-dual interior-point method.
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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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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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syre
Synchronous Reluctance (machines) - evolution
SyR-e is a Matlab/Octave package developed to design, evaluate and optimize synchronous reluctance and permanent magnet machines. To perform Finite Element Analysis (FEA) SyR-e is linked to FEMM software, and the simulation process (model creation, pre-processing, post-processing) is automatic and completely controlled from SyR-e code. For the design section, SyR-e embeds automatic procedures based on design equations, minimal FEA simulations or multi-objective optimization algorithm joined with FEA simulations. ... -
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iElectrodes
intracranial electrodes localization toolbox
iElectrodes is a free and open-source Matlab® toolbox to obtain intracranial electrode coordinates from MRI and CT images. Precise and reliable localization can be achieved fast and in a semiautomatic way with minimal user intervention. The toolbox works with ECoG (subdural grids and strips) and SEEG (depth) electrodes. The new GridFit algorithm can precisely localize high-density electrodes (up to 3mm). -
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MultiSpecEPR
MultiSpec EPR handles and present several spectra 1D and 2D
MultiSpec EPR is a program made to handle and to present several spectra (up to 4000) simultaneously or one by one as well as EPR spectra with two dimensions. It loads spectra from Bruker EPR instruments. It has a new algorithm for automatic peak picking which is very efficient and a very fast and accurate line fitting. It makes colorful figures that can be transferred directly to the scientific articles of one or multiple spectra. Save txt tables of the peaks and integrals that can be... -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
...Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts. -
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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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Math Model
Code, resources, and templates for mathematical modeling
Math_Model is a repository collecting resources, code, and algorithm templates for mathematical modeling and competition (e.g. Chinese modeling contests, US undergraduate modeling competitions). It includes LaTeX templates for writing solutions, records of past contest problems and winning solutions, algorithm implementations in MATLAB / M scripts for optimization, intelligent algorithms, numerical methods, and model frameworks. -
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Gait Tracking With x-IMU
Foot tracking algorithm demonstrated in Seb Madgwick's 3D Tracking
This repository provides the source code for a foot-tracking algorithm using an inertial measurement unit (IMU) attached to the foot, as demonstrated in Seb Madgwick’s “3D Tracking with IMU” video (March 2011). The method performs dead reckoning to integrate foot motion and corrects for drift at each foot strike (when the foot touches the ground) to reset error accumulation. The algorithm was part of gait analysis research, estimating foot trajectories in 3D over time. The repo is marked “no... -
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Enhanced SAR Compression
VOP Algorithm with improved speed and compression
***Please note that a much improved Version can be found on Github:*** https://github.com/sOrzada/VOP_Compression This work is described in: Orzada S, Fielder TM, Quick HH, Ladd ME, "A local SAR compression algorithm with improved compression, speed and flexibility", https://doi.org/10.1002/mrm.28739. This new algorithm is an iterative expansion of the exisisting local SAR compression algorithm for MRI proposed by Lee et al. ( https://doi.org/10.1002/mrm.23140) The number of...
