Document type
Bachelor thesisPublication date
Publication license
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/162237
Particle Swarm Optimization (PSO) and two real world applications
Journal Title
Authors
Director/Tutor
Journal ISSN
Volume Title
Related resource
Abstract
[en] Particle Swarm Optimization (PSO) belongs to a powerful family of optimization techniques inspired by the collective behavior of social animals. This method has shown promising results in a wide range of applications, especially in computer science. Despite this, a great popularity of such method has not been achieved.
Since we believe in the potential of PSO, we propose the following scheme to be able to take advantage of its properties. First, an implementation from scratch in C language of the method has been done, as well as an analysis of its parameters and its performance in function minimization. Then, a second more specific part
of this thesis is devoted to the adaptation of the method for solving two real-world applications. The first one, in the field of signal analysis, consists of an optimization method for the numerical analysis of Fourier functions, whereas the second, in the field of computer science, comprises the optimization of neural networks weights’
for some small architectures.
Description
Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona, Any: 2019, Tutor: Gerardo Gómez Muntané
Subject (English)
Citation
Citation
VALLS CANUDAS, Núria. Particle Swarm Optimization (PSO) and two real world applications. [consulted: 14 of June of 2026]. Available at: https://hdl.handle.net/2445/162237