Welcome to the Bio-Inspired Optimization Algorithms Repository! This repository contains implementations of various bio-inspired optimization algorithms, along with example notebooks and resources for demonstration.
This repository hosts implementations of bio-inspired optimization algorithms, which are heuristic methods inspired by principles observed in nature. These algorithms are commonly used to solve optimization problems in various fields, including engineering, computer science, finance, and biology.
- Single-layer Artificial Neural Networks (ANN)
- Multi-layer Perceptron (MLP)
- Stochastic Resonance
- ANN Classification of Digits
- Genetic Algorithm
- Quantum Genetic Algorithm (QGA)
- Coin flipping using Stochastic (SR)
- Dice rolling in Genetic Algorithm
- Coin flipping using Roulette Wheel Selection
- Stochastic Resonance for Color Images
- Geometric Shapes Recognition
- Roulette Wheel and Coin Flipping
- Video processing with SR
- Tamil, Telugu, Sanskrit character recognition
Explore the directories to find implementations of various bio-inspired optimization algorithms. Each directory typically contains Jupyter notebooks or Python scripts that demonstrate the algorithms and their applications. You can run these notebooks using Jupyter or any compatible environment.
If you'd like to contribute to this repository by adding more bio-inspired optimization algorithms, improving existing implementations, or providing additional resources, feel free to fork the repository, make your changes, and submit a pull request. Contributions are always welcome!
This repository is licensed under the MIT License. See the LICENSE file for details.