A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)
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Updated
May 21, 2024 - Python
A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)
Python microframework for building nature-inspired algorithms. Official docs: https://niapy.org
Sample Code Collection of Nature-Inspired Computational Methods
Python automated machine learning framework.
(Code) A new workload prediction model using extreme learning machine and enhanced tug of war optimization
A new metaheuristic for global optimization problems proposed in the IEEE Congress on Evolutionary Computation (CEC), 2018
Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.
The repository containing more advanced examples of usage of NiaPy micro-framework.
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine
Meta-Heuristic Algorithm for Travelling Salesman Problem
A Python Toolkit for Data Preprocessing with Evolutionary and Nature-Inspired Algorithms.
Bio-Inspired Fossil Image Segmentation for Paleontology
Firefly inspired IDS for Nature-Inspired Cyber Security
int-246-project-Twinkle0799 created by GitHub Classroom
HypONIC is a hyperparameter optimization library that uses various nature inspired computing algorithms to optimize the hyperparameters of machine learning models. The library provides a simple interface for sklearn and keras models.
Applying nature inspired ant colony optimization algorithm to solve the multiple sequence alignment problem in Julia language.
A study on swarm intelligence optimizing neural networks for workload elasticity prediction
Nature Inspired Optimization Algorithms
SPGD: Search Party Gradient Descent algorithm, a Simple Gradient-Based Parallel Algorithm for Bound-Constrained Optimization. Link: https://www.mdpi.com/2227-7390/10/5/800
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