Lamartine Almeida Teixeira

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This paper presents results of an approach to optimize architecture and weights of MLP Neural Networks, which is based on particle swarm optimization with time-varying parameters and early stopping criteria. This approach was shown to achieve a good generalization control, as well as similar or better results than other techniques, but with a lower(More)
In this paper we propose and analyze a novel method for automatic stock trading which combines technical analysis and the nearest neighbor classification. Our first and foremost objective is to study the feasibility of the practical use of an intelligent prediction system exclusively based on the history of daily stock closing prices and volumes. To this(More)
This paper presents the results of method designed to predict price trends in the stock market. Our first and foremost objective is to study the feasibility of the practical use of an intelligent prediction system exclusively based on the history of daily stock closing prices and volumes. To this end we propose a technique that consists of a combination of(More)
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