反向传播网络与ARIMA在比特币价格预测中的预测能力比较

Chung Chen, Jung-Hsin Chang, Fang-Cih Lin, Jui-Cheng Hung, Cheng-Shian Lin, Yi-Hsien Wang
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引用次数: 7

摘要

比特币是一种点对点(P2P)电子货币,可以在没有第三方管理的情况下在全球范围内进行在线支付。对股票市场的业绩预测进行了大量的研究;其中,自回归综合移动平均模型(ARIMA)是时间序列中应用最广泛的线性回归模型之一。然而,随着人工智能在现代成为一个热门的研究课题,许多研究也表明,反向传播神经网络(BPNN)在预测方面是非常有效的。因此,本文将ARIMA模型与BPNN模型在预测比特币价格方面进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Forcasting Ability between Backpropagation Network and ARIMA in the Prediction of Bitcoin Price
Bitcoin is a peer-to-peer (P2P) electronic currency that allows online payments around the world without the management of a third party. Many studies have been conducted on the performance prediction of the stock market; in particular, the Autoregressive Integrated Moving Average model (ARIMA) is one of the linear regressive models widely used in the time series. Nevertheless, as artificial intelligence has become a heated research topic in modern days, A number of studies have also shown that the Back-propagation Neural Network (BPNN) is very effective in prediction. Hence, this paper compares the ARIMA model with the BPNN model in the prediction of Bitcoin price.
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