Parallel Global Best-Worst Particle Swarm Optimization Algorithm for Solving Optimization Problems (Applied Soft Computing-2023)
Breaking transposition cipher using metaheuristic algorithms
The Jaya algorithm is a metaheuristic which is capable of solving both constrained and unconstrained optimization problems. It is a population-based method which repeatedly modifies a population of individual solutions. It is a gradient-free optimization algorithm. It does not contain any hyperparameters.
This project uses historical environmental data to accurately forecast pollution levels. By employing the Jaya optimization algorithm for parameter tuning, it significantly improves prediction precision. Built with TensorFlow.js, it supports real-time, scalable, and efficient pollution monitoring, making it a powerful tool for proactive environment
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