Standard concurrent chemoradiotherapy (CCRT) for cervical cancer achieves disease-free survival (DFS) in approximately 70% of ...

BlastGraphNet leverages a message-passing mechanism to predict overpressure and impulse load distributions on buildings with both conventional and complex geometries. The model is trained using a ...

Keywords: deep learning, power load forecasting, smart energy, sustainable urban growth, LSTM, load distribution Citation: Byeon H, AlGhamdi A, Keshta I, Soni M, Mekhmonov S and Singh G (2025) Deep ...

This repository provides an app for exploring the predictions of an image classification network using several deep learning visualization techniques. Using the app, you can: explore network ...

Keywords: building eletric load forecastng, global time series forecasting, multivariate, deep transfer learning, pre-trained models, foundation models This repository implements the experiments ...

To fill the gap, this study proposes a novel hybrid deep learning model for short-term load forecasting. First, the long short-term memory network is utilized to capture patterns from historical load ...

Short-term load forecasting is mainly utilized in control centers to explore the changing patterns of consumer loads and predict the load value at a certain time in the future. It is one of the key ...