Windfarm Optimization using Particle Swarm Optimization (Done using PySwarms) and Circle Packing.

A project in which nonogram puzzles are solved using genetic algorithms and swarm intelligence. The project compares the performance and quality of different solutions for different sizes of nonograms. The program was written in python using the pygad and pyswarms packages.

This repository focuses on optimizing a trend-based trading strategy for the EURUSD currency pair. By combining PSO and GA, the goal is to maximize returns while minimizing risk. The strategy considers buy and sell signals based on Supertrend and EMA conditions, with a fixed commission of 3 pips per trade.

PSO Algorithm Development (From Scratch and with Pyswarms)

To optimize the hyperparameters of the SVM model to maximize the accuracy. Define a function that takes the hyperparameters as input and returns the negative accuracy (since PSO minimizes the objective function) in python

SwaNN is a simple framework for neural network training with particle swarm optimization.

1D and 2D axisymmetric solvers for reaction-advection-diffusion PDE. Also includes applications: parameter sweep, parameter sensitivity analysis (SALib), parameter optimisation (PSO - pyswarms).