Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs
题名:
Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs
ISBN:
9783319733296
个人著者:
版:
1st ed. 2018.
PRODUCTION_INFO:
Cham : Springer International Publishing : Imprint: Springer, 2018.
物理描述:
XIV, 91 p. 50 illus. online resource.
系列:
SpringerBriefs in Computational Intelligence,
内容:
Introduction -- State-of-the-Art in Pattern Recognition Techniques -- SAX/GA CPU Approach -- GPU-accelerated SAX/GA -- Conclusions and Future Work in the Field.
摘要:
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. .
附加团体著者:
语言:
英文