Abstract
This chapter discusses the sequential implementation of the SAX/GA algorithm which is an algorithm designed for the optimization of market trading solutions. SAX/GA uses the SAX representation to validate the similarity between a possible solution and the training dataset, while the GA optimizes the pool of trading strategies based on a function that defines the quality of each solution. Later on, a benchmark analysis is presented in order to understand the performance of SAX/GA and locate possible regions that can take advantage of a parallel implementation.
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Baúto, J., Neves, R., Horta, N. (2018). SAX/GA CPU Approach. In: Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-73329-6_4
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DOI: https://doi.org/10.1007/978-3-319-73329-6_4
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