Promising Cryptocurrency Analysis using Deep Learning

Selim Buyrukoğlu
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引用次数: 5

Abstract

Cryptocurrency is in great demand today and there is pretty much investment in cryptocurrencies by the investors. There are more than 6000 cryptocurrencies all over the world, which clearly shows that cryptocurrency is a growing investment market. For this reason, investors having ordinary income invest in promising cryptocurrencies with a low market value. However, these investors are often unconsciously investing and making losses. At this point, sensible investments can be made using data analysis methods based on deep learning. Therefore, this study aims to analyze promising cryptocurrencies with deep learning methods. Five promising cryptocurrencies were analyzed with the ensembles of LSTM and single-based LSTM networks. This study revealed that ensembles of LSTM network do not always provide better accuracy performance than the single-based LSTM network in the analysis of promising cryptocurrencies. In other words, these two deep learning methods can be employed to obtain reliable analysis results in promising cryptocurrencies.
使用深度学习的有前途的加密货币分析
如今,加密货币需求量很大,投资者对加密货币进行了大量投资。全球有超过6000种加密货币,这清楚地表明加密货币是一个不断增长的投资市场。因此,拥有普通收入的投资者投资于市场价值较低的有前途的加密货币。然而,这些投资者往往在不知不觉中投资和亏损。此时,可以使用基于深度学习的数据分析方法进行明智的投资。因此,本研究旨在使用深度学习方法分析有前途的加密货币。利用LSTM网络和基于单一LSTM网络的组合分析了五种有前景的加密货币。本研究表明,在分析有前途的加密货币时,LSTM网络的集合并不总是比基于单一的LSTM网络提供更好的准确性性能。换句话说,这两种深度学习方法可以在有前途的加密货币中获得可靠的分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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