Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/3670
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dc.contributor.authorTanwar, Sudeepen_US
dc.contributor.authorPatel, Nisarg P.en_US
dc.contributor.authorPatel, Smit N.en_US
dc.contributor.authorPatel, Jil R.en_US
dc.contributor.authorSharma, Gulshanen_US
dc.contributor.authorDavidson, I. E.en_US
dc.date.accessioned2021-10-11T07:12:42Z-
dc.date.available2021-10-11T07:12:42Z-
dc.date.issued2021-
dc.identifier.citationTanwar, S., Patel, N.P., Patel, S.N., Patel, J.R., Sharma, G., Davidson, I.E. 2021. Deep learning-based cryptocurrency price prediction scheme with inter-dependent relations. IEEE Access. : 1-1. doi:10.1109/access.2021.3117848en_US
dc.identifier.issn2169-3536 (Online)-
dc.identifier.urihttps://hdl.handle.net/10321/3670-
dc.description.abstractBlockchain technology is becoming increasingly popular because of its applications in various fields. It gives an edge over the traditional centralized methods as it provides decentralization, immutability, integrity, and anonymity. The most popular application of this technology is cryptocurrencies, which showed a massive rise in their popularity and market capitalization in recent years. Individual investors, big institutions, and corporate firms are investing heavily in it. However, the crypto market is less stable than traditional commodity markets. It can be affected by many technical, sentimental, and legal factors, so it is highly volatile, uncertain, and unpredictable. Plenty of research has been done on various cryptocurrencies to forecast accurate prices, but the majority of these approaches can not be applied in real-time. Motivated from the aforementioned discussion, in this paper, we propose a deep-learning-based hybrid model (includes Gated Recurrent Units (GRU) and Long Short Term Memory (LSTM)) to predict the price of Litecoin and Zcash with inter-dependency of the parent coin. The proposed model can be used in real-time scenarios and it is well trained and evaluated using standard data sets. Results illustrate that the proposed model forecasts the prices with high accuracy compared to existing modelsen_US
dc.format.extent14 pen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofIEEE Accessen_US
dc.subjectCryptocurrencyen_US
dc.subjectPrice predictionen_US
dc.subjectLitecoin, Zcashen_US
dc.subjectLong Short-Term Memoryen_US
dc.subjectGated Recurrent Uniten_US
dc.subjectInter-dependenciesen_US
dc.subjectDirection algorithmen_US
dc.subjectParent coin’s directionen_US
dc.titleDeep learning-based cryptocurrency price prediction scheme with inter-dependent relationsen_US
dc.typeArticleen_US
dc.date.updated2021-10-10T13:32:24Z-
dc.identifier.doi10.1109/access.2021.3117848-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairetypeArticle-
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