cuckoo-search

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.

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

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

Nature Inspired Optimization Algorithms

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++.

数据挖掘课程项目

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

Codebase for the "Comparative Analysis of Bio-Inspired Algorithms for Disaster Recovery based on Historic Tsunami Data"

This repository contains 4 metaheuristic search algorithm for optimization

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

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

Solving different problems, using metaheuristic algorithms

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…

Metaheuristics coursework: eight labs plus a cuckoo search implementation, in Python and Jupyter

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

Metaheuristic optimization algorithms racing live on benchmark functions — 6 optimizers, animated contour plots, user-defined objective functions (safe sympy parsing), and Wilcoxon-based statistical comparison.