Search Results for "genetic algorithm matlab code"

Showing 4 open source projects for "genetic algorithm matlab code"

View related business solutions
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
    Start Free
  • 1

    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    PyGAD

    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.
    Downloads: 5 This Week
    Last Update:
    See Project
  • 3

    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...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4

    Game of Turmites

    Conway's Game of Life and Turmites Combined!

    This really isn't a game. It's all very randomly generated, and there is no way for any user input. I'll consider putting some in later. I had been wanting to make the Game of Life for some time as well as make some kind of genetic algorithm based code. So, here is what I came up with. While this may just seem like simplify a graphical display of what boredom looks like... well, it really doesn't go much past that point. If you Don't know what Conway's game of life is: It's the Black...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Build Securely on Azure with Proven Frameworks Icon
    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • Previous
  • You're on page 1
  • Next
Want the latest updates on software, tech news, and AI?
Get latest updates about software, tech news, and AI from SourceForge directly in your inbox once a month.