Parallel Global Best-Worst Particle Swarm Optimization Algorithm for Solving Optimization Problems (Applied Soft Computing-2023) ...

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 ...

In the field of optimization, many problems change over time and they are referred to dynamic optimization prob-lems (DOPs). faced with DOPs, how to adapt to environmental changes and find the optima ...

Deep convolutional neural networks (DCNNs) have achieved surpassing success in the field of computer vision, and a number of elaborately designed networks refresh the performance records in benchmark ...

5.1 Particle Swarm Optimization–Artificial Neural Network Model Implementation In the proposed study, the BP technique was replaced by the PSO algorithm to optimize the weights and biases for the ...

A MATLAB-based repository for MPPT optimization using a Hybrid Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO) algorithm in photovoltaic systems.

After highlighting the minimization of the objective function generated in the fitting process, the study revealed that a particle swarm optimization algorithm could be successfully used to identify ...

Discover how Particle Swarm Optimization algorithm can accurately determine material parameters in elastic strain-energy functions. Simulation of rubber behavior using various strain-energy functions.

The melting points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) replacing standart ...