In light of recent global shocks and rising external volatility, there is a growing need to effectively monitor short-term economic fluctuations, especially in countries with limited access to ...

Abstract: Due to the intrinsic complexity of time series forecasting within power systems, artificial intelligence has emerged as a promising pathway for predictive analytics. Although time series ...

A unified foundation model for medical time series — pretrained on open access and ethics board-approved medical corpora — offers the potential to reduce annotation burdens, minimize model ...

This project computes a Personalized Consumer Price Index (CPI) for each user based on their unique spending behavior. Instead of relying on the national “CPI-U,” this system builds a user-specific ...

1 Department of Computer Science, University of Mary Washington, Fredericksburg, USA. 2 Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, USA. This paper explores ...

Abstract: To address the limitations of traditional time series models in capturing nonlinear inflation dynamics and deep learning's susceptibility to overfitting with limited data, this study ...

This project provides a modern, well-structured implementation of hierarchical time series forecasting methods. It supports various forecasting algorithms (ARIMA, Prophet, LSTM) and reconciliation ...