Zobrazeno 1 - 10
of 486
pro vyhledávání: '"Eicker, Ursula"'
Hydrometric forecasting is crucial for managing water resources, flood prediction, and environmental protection. Water stations are interconnected, and this connectivity influences the measurements at other stations. However, the dynamic and implicit
Externí odkaz:
http://arxiv.org/abs/2409.15213
The hydrometric prediction of water quantity is useful for a variety of applications, including water management, flood forecasting, and flood control. However, the task is difficult due to the dynamic nature and limited data of water systems. Highly
Externí odkaz:
http://arxiv.org/abs/2312.05961
In recent years, graph neural networks (GNNs) combined with variants of recurrent neural networks (RNNs) have reached state-of-the-art performance in spatiotemporal forecasting tasks. This is particularly the case for traffic forecasting, where GNN m
Externí odkaz:
http://arxiv.org/abs/2209.03858
Publikováno v:
In Applied Energy 15 November 2024 374
Publikováno v:
In Energy Conversion and Management 1 November 2024 319
Publikováno v:
In Energy & Buildings 1 September 2024 318
A geographic-semantic context-aware urban commuting flow prediction model using graph neural network
Publikováno v:
In Expert Systems With Applications 1 February 2025 261