AI model improves flood forecasting with higher accuracy than current methods

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...
Tech Xplore

Hybrid AI model combines graphs and transformers for real-time traffic forecasts

Urban congestion is a big problem in our cities. It leads to commuter delays and economic inefficiency. More tragically, though, it leads to a million deaths annually worldwide. Research appearing in ...

Clustering-based AI forecasts river water levels using just a few long records

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...
IEEE

Leveraging Knowledge Graph and Large Language Model Synergies for Intelligent Fault Analysis in Urban Rail Transit Signaling Systems

Abstract: To address the challenges of insufficient text data utilization and low manual diagnosis efficiency in urban rail transit signaling system fault analysis, particularly the difficulty in ...
IEEE

Research on Knowledge- and Data-Driven Collaborative Gear Degradation State Prediction Model Based on KDPINN

Abstract: Because of the complex and multifactorial nature of gear degradation, purely data-driven prediction models are often limited by their closed box characteristics, resulting in low reliability ...