Conclusions: Prevalence of obesity is increasing, and use of GLP-1 RAs as the preferred antiobesity medication has increased ...

Oversimplifies trends and ignores real-world disruptions. Can’t predict economic downturns, competitor actions and shifts in customer behavior on its own. Ignores randomness; every forecast will have ...

UGA's Weather Dawgs use a high-resolution model to create localized forecasts for Athens, improving accuracy for residents.

Abstract: This paper introduces a new hybrid time series forecasting technique to obtain an efficient and accurate daily crude oil prices forecast. The proposed hybrid technique combines the features ...

I am attempting to set up the project on a fresh macOS environment with Python 3.12. I've encountered a dependency deadlock that prevents the model from running. We likely need to re-pickle the ...

Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan ...

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

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

Sometimes, reading Python code just isn’t enough to see what’s really going on. You can stare at lines for hours and still miss how variables change, or why a bug keeps popping up. That’s where a ...