GA-PSO Integration Algorithm and Its Application in Modeling on Furnace Pressure System

DOI

10.2991/wartia-16.2016.212How to use a DOI?

Keywords

particle swarm optimization algorithm, genetic algorithm, system identification, furnace pressure system.

Abstract

PSO algorithm is a kind of swarm intelligence optimization algorithm which has the advantages of simple principle, easy implementation, few parameters needed to adjust and so on. However, the search accuracy of the basic PSO algorithm still needs to be improved. In this paper, a modified PSO algorithm using exponent decline inertia weight is put forward and successfully applied to the parameter identification of the furnace pressure system. This modified PSO algorithm combines the nonlinear optimization and genetic algorithm to optimize the inertia weight and acceleration constants of the basic PSO algorithm, and is proved to be effective in parameter identification.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Qiming Chen
PY  - 2016/05
DA  - 2016/05
TI  - GA-PSO Integration Algorithm and Its Application in Modeling on Furnace Pressure System
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1001
EP  - 1004
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.212
DO  - 10.2991/wartia-16.2016.212
ID  - Chen2016/05
ER  -