Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs

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...

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Detaylı Bibliyografya
Asıl Yazarlar: Baúto, João (Yazar), Neves, Rui (Yazar), Horta, Nuno (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Seri Bilgileri:SpringerBriefs in Computational Intelligence,
Konular:
Computational intelligence.
Financial engineering.
Social sciences > Mathematics.
Computational Intelligence.
Financial Engineering.
Mathematics in Business, Economics and Finance.
Online Erişim:Full-text access
Diğer Bilgiler
Özet: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. .
Fiziksel Özellikler:XIV, 91 p. 50 illus. online resource.
ISBN:9783319733296
ISSN:2625-3712
DOI:10.1007/978-3-319-73329-6

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