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Adaptive Parameter Selection in Comprehensive Learning Particle Swarm Optimizer
ADE-MOAIS Optimization
Automatic LDR Based Night Lamp.
breast cancer feature selection using binary particle swarm optimization
SVM for Breast Cancer Detection from mammogram Using MatLAB
All nature-inspired algorithms involve two processes namely exploration and exploitation. For getting optimal performance, there should be a proper balance between these processes. Further, the majority of the optimization algorithms suffer from local minima entrapment problem and slow convergence speed. To alleviate these problems, researchers are
ActiveState Code Recipes
Compare a variety of MOEA to solve the ModCell multiobjecitve strain desing problem
The Matlab Source code of the Competitive Swarm Optimizer (CSO)
Distributed Evolutionary Algorithms in Python
# Introduction of DNN-AR-MOEA This repository contains code necessary to reproduce the experiments presented in Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network. Gaussian processes are widely used in surrogate-assisted evolutionary optimization of expensive problems. We propose a computationally efficient dropout neural network (EDN) to replace the Gaussian process and a new model management strategy to achieve a good balance between convergence and diversity for assisting evolutionary algorithms to solve high-dimensional multi- and many-objective expensive optimization problems. mainlydue to the ability to provide a confidence level of their outputs,making it possible to adopt principled surrogate managementmethods such as the acquisition function used in Bayesian opti-mization. Unfortunately, Gaussian processes become less practi-cal for high-dimensional multi- and many-objective optimizationas their computational complexity is cubic in the number oftraining samples. # References If you found DNN-AR-MOEA useful, we would be grateful if you cite the following reference: Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network (IEEE Transactions on Systems, Man and Cybernetics: Systems).
Economic Dispatching by Bees Algorithm
This repo contains the codes and supplementary documents for Embedded Chaotic Whale Survival Algorithm
Source Code of Evolutionary Multiobjective Optimization Based Multimodal Optimization
classical engineering design problems single objective fitness function pressure vessel welded beam and tension/compression spring design optimization problems
This project creates a hybrid algorithm named Honey Badger-Harris Hawk Optimizer which is capable of solving optimization tasks.
"Explore the world of Evolutionary Algorithms (EAs) with this educational repository. Dive into detailed implementations from Genetic Algorithms to Particle Swarm Optimization. Designed for clarity and understanding, it's a comprehensive guide for learners and educators alike. Dive in and demystify EAs!"
A noval feature selection method similar to pagerank method, and ultilized Bayesian optimization to search appropriate parameters
Code for Feature Selection
灰狼优化算法(GWO)路径规划、轨迹规划、轨迹优化、多智能体/多无人机航迹规划
Using GreyWolfOptimization for feature selection and multi kernel SVM for classification for Malware Hunting on IoT devices
Sanitized Grey Wolf Optimizer(SGWO)-Support Vector Regressor (SVR)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.