Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer

Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer

This research delves into the obstacles and difficulties associated with predicting cryptocurrency movements in the volatile global financial market. This study develops and evaluates an advanced Deep Learning-Enhanced Temporal Fusion Transformer (ADE-TFT) model to estimate Bitcoin values more accur...

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Bibliographic Details
Main Authors: Arslan Farooq, M. Irfan Uddin, Muhammad Adnan, Ala Abdulsalam Alarood, Eesa Alsolami, Safa Habibullah
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Heliyon
Subjects:
Block chain
Deep learning
Cryptocurrency
Sentiment analysis
Artificial intelligence
Transformers
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024161737
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