Particle Swarm Optimisation Classical and Quantum Perspectives

Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world application...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Sun, Jun, Lai, Choi-Hong, Wu, Xiao-Jun
Format: E-Book Buch
Sprache:Englisch
Veröffentlicht: Boca Raton CRC Press 2012
Taylor & Francis Group
Ausgabe:1
Schriftenreihe:Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series
Schlagworte:
COMPUTERS / Programming / Algorithms. bisacsh
Mathematical optimization
MATHEMATICS / General. bisacsh
MATHEMATICS / Number Systems. bisacsh
Particles (Nuclear physics)
Swarm intelligence
Rosenbrock Function
Time Complexity
Log Odds Scores
SVM Model
Dielectric Resonator Antennas
QPSO
ED Problem
Schwefel’s Problem
Gbest Position
MSA Problem
Original PSO
Hybrid PSO
Adaptive Inertia Weight
Position Update Equation
PSO Method
Rastrigin Function
Solve ED Problem
Schwefel Function
QPSO Algorithm
Benchmark Functions
PSO Algorithm
Random Search Method
Chen System
HMM Training
Inertia Weight
ISBN:9781439835760, 1439835764
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world applications, including inverse problems, digital filter d.
Bibliographie:Includes bibliographical references and index
ISBN:9781439835760
1439835764
DOI:10.1201/b11579