Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs
Titre:
Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs
ISBN (Numéro international normalisé des livres):
9783319733296
Auteur personnel:
Edition:
1st ed. 2018.
PRODUCTION_INFO:
Cham : Springer International Publishing : Imprint: Springer, 2018.
Description physique:
XIV, 91 p. 50 illus. online resource.
Collections:
SpringerBriefs in Computational Intelligence,
Table des matières:
Introduction -- State-of-the-Art in Pattern Recognition Techniques -- SAX/GA CPU Approach -- GPU-accelerated SAX/GA -- Conclusions and Future Work in the Field.
Extrait:
This Brief presents a study of SAX/GA, an algorithm to optimize market trading strategies, to understand how the sequential implementation of SAX/GA and genetic operators work to optimize possible solutions. This study is later used as the baseline for the development of parallel techniques capable of exploring the identified points of parallelism that simply focus on accelerating the heavy duty fitness function to a full GPU accelerated GA. .
Auteur collectif ajouté:
Accès électronique:
Full Text Available From Springer Nature Engineering 2018 Packages
Langue:
Anglais