数字货币投资预测器综述

Rane Nikita, S. Subhashini, Yashwin B S, Vishal K Vavle, Darshan A
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引用次数: 1

摘要

加密货币是一种计算机化的货币方式,交易在网络空间完成。这是一种数字/软货币,不像纸币,它们不是硬拷贝。强调各种分散的货币,没有任何第三方参与,从而确保用户可以获得所有服务。由于汇率的高度波动影响着国际贸易和关系。以太坊,瑞波币,比特币,莱特币这些存在的流行货币的例子。每年都会对流行的加密货币比特币,瑞波币,以太坊进行研究。使用深度学习模型即栅格循环单元(GRU)和长短期记忆(LSTM)来改进预测方法的有效方法。该研究致力于利用机器学习和数据科学预测加密货币价格的相关问题。主要使用的算法有:RNN和GRU。该数据集将包括流行的加密货币的过去价格信息,例如:比特币,以太坊和Ripple。LSTM、RNN和GRU算法已经存在,可以预测未来的价格行为,但可预测性低于标准。主要目标是将RNN和GRU算法结合起来形成混合算法,并可能提高预测的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Digital Coin Investing Predictor
Cryptocurrency is a computerized method of money where transactions are done in the cyber space. This is a digital/soft currency, unlike currency notes they are not hard copies. Emphasizing the varieties of currencies that are decentralized and do not have any third party involvement, therefore ensuring that users can get all the services. Because of the high volatility the currency impacts the international trade and relations. Etherium, Ripple, Bitcoin, Litecoin some examples of popular currencies that exists. The study on popular cryptocurrencies Bitcoin, Ripple, Etherium are performed every year. An effective way to improve the method of predictions using deep learning models namely Grated Reccurrent Unit (GRU) and Long Short-Term Memory (LSTM). The research is devoted to the problems related to predicting crypto currency prices using machine learning and data science. The main algorithms used are: RNN and GRU. The data set will include the past price information from the popular crypto currencies for example: Bitcoin, Ethereum and Ripple. LSTM, RNN and GRU algorithms already exist to predict the future price action but the predictability rate is subpar. The main goal is to combine RNN and GRU Algorithms to form a hybrid and possibly increase the accuracy of the predictions.
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