Treffer: Adaptive velocity threshold particle swarm optimization
Title:
Adaptive velocity threshold particle swarm optimization
Authors:
Source:
Rough sets and knowledge technology (First international conference, RSKT 2006, Chongqing, China, July 24-26, 2006)Lecture notes in computer science. :327-332
Publisher Information:
Berlin; New York: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 10 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Méthode adaptative, Adaptive method, Método adaptativo, Optimisation essaim particule, Swarm intelligence, Optimización enjambre partícula, Réseau neuronal, Neural network, Red neuronal, Théorie ensemble approximatif, Rough set theory, Théorie programmation, Programming theory
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University, Xi'an,710049, China
Division of System Simulation and Computer Application Taiyuan University of Science and Technology, 030024, Cui-Zhi-Hua, China
Division of System Simulation and Computer Application Taiyuan University of Science and Technology, 030024, Cui-Zhi-Hua, China
ISSN:
0302-9743
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19131774
Database:
PASCAL Archive
Weitere Informationen
Particle swarm optimization (PSO) is a new robust swarm intelligence technique, which has exhibited good performance on well-known numerical test problems. Though many improvements published aims to increase the computational efficiency, there are still many works need to do. Inspired by evolution programming theory, this paper proposes a new adaptive particle swarm optimization in which the velocity threshold dynamically changes during the course of a simulation. Seven benchmark functions are used to testify the new algorithm, and the results showed clearly the new adaptive PSO leads to a significantly better performance, although the performance improvements were found to be dependent on problems.