Table 2 Analysis of GRU model architecture for fault detection in NEVs.
From: Enhancing fault detection in new energy vehicles via novel ensemble approach
Layer (Type) | Output Shape | Parameters |
|---|---|---|
GRU (gru_12) | (None, 10, 128) | 52,608 |
Dropout (dropout_25) | (None, 10, 128) | 0 |
GRU (gru_13) | (None, 64) | 37,248 |
Dropout (dropout_26) | (None, 64) | 0 |
Dense (dense_44) | (None, 32) | 2,080 |
Dense (dense_45) | (None, 4) | 132 |
Total Parameters | 92,068 (359.64 KB) | |
Trainable Parameters | 92,068 (359.64 KB) | |
Non-trainable Parameters | 0 (0.00 B) |
