Spatial data generalisation is a critical process in cartography and geographic information science, enabling the simplification of complex geospatial datasets while retaining essential structural and ...

Recent advancements in neural network methodologies have revolutionised hydrological forecasting, enabling more accurate, robust and computationally efficient predictions of water resource dynamics.

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...