A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)
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Updated
Jun 12, 2024 - Python
A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python
Proposing a novel approach on using Naives Bayes by using Robust Kernel Density Estimation (RKDE) and optimising the bandwith(h) with Harris Hawks Optimization (HHO)
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.
Penerapan Harris Hawks Optimization Pada Capacitated Vehicle Routing Problem
The biggest module developed with complete focus on Feature Selection (FS) using Meta-Heuristic Algorithm / Nature-inspired evolutionary / Swarm-based computing.
Implement the-state-of-the-art meta-heuristic algorithms using python (numpy)
Matlab implementation of the article: A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques
Multilevel thresholding segmentation method
Efficient Time-series Forecasting using Neural Network and Opposition-based Coral Reefs Optimization
This repository contains the Harris Hawks Optimization code (matlab M-file) for optimizing the benchmark function.
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.
The binary version of Harris Hawk Optimization (HHO), called Binary Harris Hawk Optimization (BHHO) is applied for feature selection tasks.
Harris Hawks Optimization (HHO) - Python Code
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