智能算法-遗传算法、蚁群算法、粒子群算法实现。实现版本Java,Python,MatLab多版本实现

遗传算法 - Matlab

This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

Matlab Module for Stock Market Prediction using Simple NN

MATLAB Tool for Multi-Objective Optimization

Genetic Algorithms Toolbox

毕设文章以及文中的MATLAB，以及那段时间帮同学们写的MATLAB编码。元胞自动机(Cellular Automata)，遗传算法(Genetic Algorithm)。⬅↖⬆↗➡↘⬇↙↪↩🔄🧡💛💙💚💜🖤💕💞💖💝💥

A very simple Genetic Algorithm implementation for matlab, easy to use, easy to modify runs fast.

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 optim…

NSGA-III: Non-dominated Sorting Genetic Algorithm, the Third Version — MATLAB Implementation

Controlling a nonholonomic robot to follow a trajectory with a modified PID Controller.

Intelligent deployment strategies for heterogeneous nodes to increase the network lifetime of wireless sensor networks.

A genetic Algorithm Solution for Weekly Course Timetabling Problem

This MATLAB project implements a hybrid optimization algorithm that combines Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The algorithm is designed to optimize a set of parameters (genes) for various problems, making it flexible and adaptable to different optimization scenarios.

(CUMCM2018)Adaptive genetic algorithm based on improved harmony algorithm

Genetic-algorithm-based optimisation of resonator dispersion for tailoring Kerr comb states of the Lugiato-Lefever Equation (LLE).

Image contrast enhancement via a hybrid of ant colony optimization, genetic algorithm, and simulated annealing

Obtaining the best coefficients of Inverse Dynamics Controller, for a dynamical system, with Optimization Algorithms.

A data prediction neural network model optimized with genetic algorithm//遗传算法优化的预测模型

Implementation of a genetic algorithm to determine the parameters of the PID, PI-D, I-PD and PIDA controllers in order to compensate various benchmark processes, which are representative of many industrial applications. In particular, by considering separately a set-point and a load disturbance rejection unit step response the IAE is minimized b…