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Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs
Author
Title
Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs [electronic resource] / by João Baúto, Rui Neves, Nuno Horta.
ISBN
9783319733296
Publication
Cham : Springer International Publishing : Imprint: Springer, 2018.
Physical Description
1 online resource (XIV, 91 p.) 50 illus.
Local Notes
Access is available to the Yale community.
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Access restricted by licensing agreement.
Summary
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. .
Variant and related titles
Springer ebooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
May 07, 2018
Series
SpringerBriefs in Applied Sciences and Technology,
Contents
Introduction
State-of-the-Art in Pattern Recognition Techniques
SAX/GA CPU Approach
GPU-accelerated SAX/GA
Conclusions and Future Work in the Field.
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