Objective: To compare the application of the ARIMA model, the Long Short-Term Memory (LSTM) model and the ARIMA-LSTM model in forecasting foodborne disease incidence. Methods: Monthly case data of ...

Abstract: Earthquake forecasting using traditional methods remains a complex task due to the inherent nonlinearity and stochastic nature of seismic activity. Therefore, this study examines the ...

The company has since taken down the image of the accused killer. Fast fashion giant Shein is conducting an investigation of its internal processes after using the likeness of Luigi Mangione to model ...

Background Improving small and sick newborn care (SSNC) is crucial in resource-limited settings. Newborn Essential Solutions and Technologies (NEST360), a multicountry alliance, aims to reduce newborn ...

Background: Accurate forecasting of lung cancer incidence is crucial for early prevention, effective medical resource allocation, and evidence-based policymaking. Objective: This study proposes a ...

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...

One of the biggest issues with large language models (LLMs) is working with your own data. They may have been trained on terabytes of text from across the internet, but that only provides them with a ...

1 Department of Meteorology, School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China. 2 Tanzania Meteorological Authority, Dodoma, Tanzania. 3 School of ...