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)

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

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.

Nature Inspired Optimization Algorithms

Implemented fully documented Cuckoo Search Optimization algorithm via Levy Flights (basic model) using Python programming language

Metaheuristic(Genetic algorithm, Particle swarm optimization, Cuckoo search, Grey wolf optimizer), Reinforcement Learning with Python

Neuromorphic Project : Pattern Classification using Cuckoo Search Algorithm and Levy Flight Model

different algorithms to find population close to the optimal fitness, including genetic algorithm, differential evolution algorithm, PSO, firefly algorithm, cuckoo search algorithm and whale optimization algorithm in C++.

Expandable Cuckoo hash map/set implementation in Go (Docs WIP)

Implementation of IIR and FIR digial filter optimization using ABC, Cuckoo Search and Particle Search Algorithm

数据挖掘课程项目

The Repository dedicated to code and more for Swarm Intelligence furthermore.

This repository contains 4 metaheuristic search algorithm for optimization

Best solutions for Natural Computing 2023/2024

Solving different problems, using metaheuristic algorithms

Solutions for Labs of Nature Inspired Computing course offered at Innopolis University

This project aimed to implement three well-known meta-heuristic algorithms: cuckoo search (CS), bat algorithm (BA), and flower pollination algorithm (FPA). We found that three algorithms could have a promising performance generally. It might need more runs to be converged when training BA. The time cost of BA was the highest while the difference…

This repository offers a movie recommendation system that uses Neural Collaborative Filtering and Non-negative Matrix Factorization (NNMF) for generating user-item matrices, combined with Cuckoo-Search and K-means clustering for optimization. The algorithm leverages collaborative filtering to make fast movie suggestions based on single preferences

Trabajo Final de la asignatura del Master Universitario en Inteligencia Artificial de la Universidad Politécnica de Madrid

R implementation of "Engineering Optimisation by Cuckoo Search"