Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3034
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dc.contributor.authorAshikul Islam, M. D-
dc.date.accessioned2022-10-06T05:34:13Z-
dc.date.available2022-10-06T05:34:13Z-
dc.date.issued2022-02-11-
dc.identifier.issn5961-5011-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3034-
dc.description.abstractTechnology has significantly reshaped how humans interact with their tangible and intangible surroundings. Cryptocurrency is considered to be one of the most recent technological inventions which revolutionized how we perceive currencies and their functionality. It has become popular because of its safety, security and anonymity. However, volatility remains one of the major issues with cryptocurrencies to this day. Therefore, the primary aim of this paper is to develop LSTM (Long ShortTerm Memory), GRU (Gated Recurrent Units) and a Stacking Ensemble Learning algorithm that efficiently predicts the price of a cryptocurrency for a given period of time. The predictions are then observed and analysed to determine the comparative performance of the said algorithms.en_US
dc.language.isoenen_US
dc.publisherSLIITen_US
dc.relation.ispartofseriesProceedings of the SLIIT International Conference On Engineering and Technology,;Vol. 01-
dc.subjectCryptocurrencyen_US
dc.subjectLSTMen_US
dc.subjectGRUen_US
dc.subjectStacking Ensembleen_US
dc.subjectNeural Networken_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.titleCryptocurrency Price Prediction: A Comparative Study using LSTM, GRU and Stacking Ensemble Algorithm for Time Series Forecastingen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.54389/NTPV9785-
Appears in Collections:Proceedings of the SLIIT International Conference On Engineering and Technology Vol. 01(SICET) 2022

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