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This repository implements several swarm optimization algorithms and visualizes them. Implemented algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Cuckoo Search (CS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)
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
The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented to perform optimization. This is the source codes of the paper: S. Mirjalili, S. M. Mirjalili, A. Lewis, Grey Wolf Optimizer, Advances in Engineering Software, Volume 69, March 2014, Pages 46-61, ISSN 0965-9978, http://dx.doi.org/10.1016/j.advengsoft.2013.12.007. More information can be found in: http://www.alimirjalili.com/GWO.html
This MATLAB code implements the binary Grass hopper optimization algorithm to select the features and train with KNN
Transaction fraud detection using machine learning and nature inspired algorithms.
Java Evolutionary Multi-Objective Algorithm
A speaker recognition algorithm with GWO and PSO.
Circle Detection on Images using Grey Wolf Optimizer