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Updated: Jun 6, 2025

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可解释的多地平线时间序列预测加密货币通过杆时间融合变压器

Arslan Farooq1, M Irfan Uddin1, Muhammad Adnan1

  • 1Institute of Computing, Kohat University of Science and Technology, Kohat, 26000, KP, Pakistan.

Heliyon
|December 2, 2024
PubMed
概括

本研究介绍了一种先进的深度学习增强时间融合变压器 (ADE-TFT) 模型,用于更准确的比特币价格预测. 与传统方法相比,ADE-TFT模型显著提高了加密货币预测的准确性.

关键词:
人工智能的人工智能是人工智能.区块链的区块链链是什么加密货币 加密货币.深度学习是一种深度学习.情绪分析是一种情绪分析.时间数据 时间数据变压器 变压器 变压器

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