Integrating IoT data and reinforcement learning for adaptive macroeconomic policy optimization

Integrating IoT data and reinforcement learning for adaptive macroeconomic policy optimization

Macroeconomic policy optimization is essential in today’s complex economic environments, yet existing models often struggle to effectively utilize high-frequency IoT data alongside traditional low-frequency indicators, limiting responsiveness to rapid changes. To address this, we propose MLD-Net, a...

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Bibliographic Details
Main Authors: Cong Peng, Yongshan Zhang, Liheng Jiang
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Alexandria Engineering Journal
Subjects:
Macroeconomic policy optimization
IoT data
Mixed-frequency data
MIDAS regression
LSTM networks
Deep Q-network
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016825000924
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