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一种整体方法,集成LSTM和ARIMA模型,用于增强金融市场预测

Lesia Mochurad1, Andrii Dereviannyi1

  • 1Department of Artificial Intelligence, Lviv Polytechnic National University, Kniazia Romana str., 5, Lviv 79905, Ukraine.

Royal Society open science
|September 12, 2024
PubMed
概括

本研究介绍了一种整体财务预测模型,该模型结合了长期短期记忆 (LSTM) 和自行回归集成移动平均线 (ARIMA),以提高准确性并降低复杂市场的风险.

关键词:
组合学习组合学习金融市场是金融市场.预测 预测 预测 预测机器学习是机器学习.神经网络的神经网络的神经网络

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