Tag: Artificial neural network
Graph neural networks identified flood-vulnerable river segments
Graph neural network framework for assessing flood vulnerability in river basins. Identifies high-risk segments and flood-prone sub-basins by combining hydrological attributes with network topology.
RNN-based distortion models improved CAT bond pricing
Catastrophe bond pricing framework combining distortion operator theory with recurrent neural networks, capturing discontinuous repricing and tail-risk compensation.
Lower bit depth reduced speaker recognition accuracy
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Quantization of neural network output tensors reduces storage for speaker recognition databases. Study evaluates bit depth reduction impacts on recognition accuracy across three architectures.
