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 ...

Research Department, Guangdong Service Center for Veterans, Guangzhou, Guangdong, China To tackle these challenges, this study introduces a Feature Pyramid Space Transformation (FPST) within a ...

Abstract: Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements ...

A forecasting study published in Pharmacoeconomics and Policy analyzes the impact of the Inflation Reduction Act (IRA) on diabetes drug costs for Medicare in Louisiana, USA. The authors found that ...

In the evolving ecosystem of prediction markets, Kalshi Inc. has quickly emerged as a significant force, recently highlighting research that positions its platform as a potentially superior tool for ...

A) Retail/E-commerce inventory (forecasting product demand for stores or online sales) B) Manufacturing raw materials (forecasting material needs for production) C) Distribution/logistics (forecasting ...

“Stranger Things” fans are counting down the minutes to the Netflix series's final episode on New Year's Eve. "Stranger Things" returned to Hawkins, Indiana, after a three-year wait on Nov. 26 when it ...