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.

An implementation of various metaheuristics adapted to train neural networks

This is a playground for learning and working with various Optimization algorithms with a focus on real life applications.

Project to improve the efficiency of traffic signal control and reduce traffic delay at intersections by using various optimization algorithms.

UR3 Inverse Kinematics by Bat Algorithm

CS F407 Project

Brain Tumor Diagnosis using MRI is a machine learning project that detects brain tumors from MRI scans. It involves preprocessing steps like normalization and Gaussian filtering, followed by feature extraction using GLCM and feature selection using the BAT algorithm. An SVM classifier is then used to accurately classify the presence of tumors.

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…

ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction