In the present study, the modified discrete particle swarm optimization method was invoked to adaptively configure the globally optimal CART (MPSOCART) via simultaneously selecting the optimal ...

The approach integrates the advantages of Proportional-Integral-Derivative control, particle swarm optimization, and neural networks. By constructing a neural network model with input, hidden, and ...

optimization genetic-algorithm artificial-intelligence simulated-annealing tsp particle-swarm-optimization pso travelling-salesman-problem fish-swarms immune ant-colony-algorithm heuristic-algorithms ...

The performance of the well-known particle swarm optimization (PSO) method can be improved by minimizing the possibility of premature convergence in a local minimum. We can achieve this by modifying ...

Particle swarm optimization (PSO) algorithm is an optimization technique with remarkable performance for problem solving. The convergence analysis of the met ...

Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature. Although the original PSO has shown good optimization performance, it still severely ...

This work investigates the potential of the particle swarm algorithm for the optimization of detailed kinetic mechanisms. To this end, empirical analysis has been conducted to evaluate the efficiency ...

This Python simulation employs Particle Swarm Optimization (PSO) to model the exploration of an unknown environment by a swarm of robots. The robots aim to converge on the global best position, ...