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Biologically Inspired Algorithms for Financial Modelling
Anthony Brabazon Michael O’Neill
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
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Disponibilidad
Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
---|---|---|---|---|
No detectada | 2006 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-26252-7
ISBN electrónico
978-3-540-31307-6
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2006
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2006
Cobertura temática
Tabla de contenidos
Wrap-up
Anthony Brabazon; Michael O’Neill
The key learning mechanisms in the PSO algorithm are driven by a metaphor of social behaviour: that good solutions uncovered by one member of a population are observed and copied by other members of the population. Of course, these learning mechanisms abound in business and other social settings. Good business strategies, good product designs, and good theories stimulate imitation and subsequent adaptation. Particle swarm algorithms have proven to be successful optimisation tools in a variety of applications, and they have clear potential for application to financial modelling.
Part III - Case Studies | Pp. 255-255