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Hierarchical Temporal Memory Theory Approach to Stock Market Time Series Forecasting
2021
Electronics
Over the years, and with the emergence of various technological innovations, the relevance of automatic learning methods has increased exponentially, and they now play a key role in society. More specifically, Deep Learning (DL), with the ability to recognize audio, image, and time series predictions, has helped to solve various types of problems. This paper aims to introduce a new theory, Hierarchical Temporal Memory (HTM), that applies to stock market prediction. HTM is based on the
doi:10.3390/electronics10141630
fatcat:dkzwmy5mpnft3os5jsmdf2t2r4